./ohML loading 

float inhale_rate = 0.5;
float exhale_rate = 1.0;
while(1) { 
    // Inhale phase
    for(float i = 0; i <= 1; i += inhale_rate) {
        printf("\rInhaling... (%f%%)\n", i * 100);
        sleep(1); // Sleep for 1 second to simulate time passing
    }

    // Pause between inhale and exhale
    printf("\rPausing...\n");
    sleep(2);

    // Exhale phase
    for(float i = 1; i >= 0; i -= exhale_rate) {
                    printf("\rExhaling... (%f%%)\n", i * 100);
                    sleep(1); // Sleep for 1 second to simulate time passing
    }

    // Pause between exhale and inhale
    printf("\rPausing...\n");
    sleep(2);
}

double x_min = -2.0;
double y_min = -1.5;
double x_max = 1.0;
double y_max = 1.5;

for (int j = 0; j < height; ++j) {
    for (int i = 0; i < width; ++i) {
        std::complex<double> 
            c((x_min + (x_max - x_min) * i / (width - 1)), 
                ((y_min + (y_max - y_min)) * j) / (height - 1));

        int iter = 0;
        std::complex<double> z(0, 0);

        while (std::abs(z) <= 2 && iter < 255) {
                z = z * z + c;
                ++iter;
        }

        unsigned char color[] = {
            static_cast<unsigned char>(iter % 8 * 32),
            static_cast<unsigned char>(iter % 16 * 17),
            static_cast<unsigned char>(iter % 32 * 14)
        };
        file.write(reinterpret_cast<char*>(color), sizeof(color));
    }
}

using ll = long long;
const ll INF = (1LL<<62);
vector<ll> dist(n, INF);
priority_queue<pair<ll,int>, vector<pair<ll,int>>, greater<pair<ll,int>>> pq;

dist[s] = 0;
pq.push({0, s});
while (!pq.empty()) {
    auto [d, u] = pq.top(); pq.pop();
    if (d != dist[u]) continue;
    for (auto [v, w] : g[u]) {
        if (dist[v] > d + w) {
            dist[v] = d + w;
            pq.push({dist[v], v});
        }
    }
}

struct DSU {
    vector<int> p, r;
    DSU(int n): p(n), r(n,0) { iota(p.begin(), p.end(), 0); }
    int find(int a){ return p[a]==a? a : p[a]=find(p[a]); }
    bool unite(int a,int b){
        a=find(a); b=find(b);
        if(a==b) return false;
        if(r[a]<r[b]) swap(a,b);
        p[b]=a;
        if(r[a]==r[b]) r[a]++;
        return true;
    }
};

vector<int> pi(const string& s){
        int n=s.size();
        vector<int> p(n);
        for(int i=1;i<n;i++){
                int j=p[i-1];
                while(j>0 && s[i]!=s[j]) j=p[j-1];
                if(s[i]==s[j]) j++;
                p[i]=j;
        }
        return p;
}

struct BIT {
        int n; vector<long long> bit;
        BIT(int n): n(n), bit(n+1,0) {}
        void add(int i,long long v){ for(++i;i<=n;i+=i&-i) bit[i]+=v; }
        long long sum(int i){ long long r=0; for(++i;i>0;i-=i&-i) r+=bit[i]; return r; }
};

vector<int> nge(n, -1);
stack<int> st;
for(int i=0;i<n;i++){
        while(!st.empty() && a[st.top()] < a[i]){
                nge[st.top()] = i;
                st.pop();
        }
        st.push(i);
}

queue<int> q;
for(int i=0;i<n;i++) if(indeg[i]==0) q.push(i);
vector<int> order;
while(!q.empty()){
        int u=q.front(); q.pop();
        order.push_back(u);
        for(int v: adj[u]){
                if(--indeg[v]==0) q.push(v);
        }
}

struct Seg {
        int n; vector<long long> t;
        Seg(int n): n(n), t(4*n, INF) {}
        void upd(int v,int tl,int tr,int pos,ll val){
                if(tl==tr){ t[v]=val; return; }
                int tm=(tl+tr)/2;
                if(pos<=tm) upd(v*2,tl,tm,pos,val);
                else upd(v*2+1,tm+1,tr,pos,val);
                t[v]=min(t[v*2],t[v*2+1]);
        }
        ll qry(int v,int tl,int tr,int l,int r){
                if(l>r) return INF;
                if(l==tl && r==tr) return t[v];
                int tm=(tl+tr)/2;
                return min(qry(v*2,tl,tm,l,min(r,tm)),
                                      qry(v*2+1,tm+1,tr,max(l,tm+1),r));
        }
};
float inhale_rate = 0.5;
float exhale_rate = 1.0;
while(1) { 
    // Inhale phase
    for(float i = 0; i <= 1; i += inhale_rate) {
        printf("\rInhaling... (%f%%)\n", i * 100);
        sleep(1); // Sleep for 1 second to simulate time passing
    }

    // Pause between inhale and exhale
    printf("\rPausing...\n");
    sleep(2);

    // Exhale phase
    for(float i = 1; i >= 0; i -= exhale_rate) {
                    printf("\rExhaling... (%f%%)\n", i * 100);
                    sleep(1); // Sleep for 1 second to simulate time passing
    }

    // Pause between exhale and inhale
    printf("\rPausing...\n");
    sleep(2);
}

double x_min = -2.0;
double y_min = -1.5;
double x_max = 1.0;
double y_max = 1.5;

for (int j = 0; j < height; ++j) {
    for (int i = 0; i < width; ++i) {
        std::complex<double> 
            c((x_min + (x_max - x_min) * i / (width - 1)), 
                ((y_min + (y_max - y_min)) * j) / (height - 1));

        int iter = 0;
        std::complex<double> z(0, 0);

        while (std::abs(z) <= 2 && iter < 255) {
                z = z * z + c;
                ++iter;
        }

        unsigned char color[] = {
            static_cast<unsigned char>(iter % 8 * 32),
            static_cast<unsigned char>(iter % 16 * 17),
            static_cast<unsigned char>(iter % 32 * 14)
        };
        file.write(reinterpret_cast<char*>(color), sizeof(color));
    }
}

using ll = long long;
const ll INF = (1LL<<62);
vector<ll> dist(n, INF);
priority_queue<pair<ll,int>, vector<pair<ll,int>>, greater<pair<ll,int>>> pq;

dist[s] = 0;
pq.push({0, s});
while (!pq.empty()) {
    auto [d, u] = pq.top(); pq.pop();
    if (d != dist[u]) continue;
    for (auto [v, w] : g[u]) {
        if (dist[v] > d + w) {
            dist[v] = d + w;
            pq.push({dist[v], v});
        }
    }
}

struct DSU {
    vector<int> p, r;
    DSU(int n): p(n), r(n,0) { iota(p.begin(), p.end(), 0); }
    int find(int a){ return p[a]==a? a : p[a]=find(p[a]); }
    bool unite(int a,int b){
        a=find(a); b=find(b);
        if(a==b) return false;
        if(r[a]<r[b]) swap(a,b);
        p[b]=a;
        if(r[a]==r[b]) r[a]++;
        return true;
    }
};

vector<int> pi(const string& s){
        int n=s.size();
        vector<int> p(n);
        for(int i=1;i<n;i++){
                int j=p[i-1];
                while(j>0 && s[i]!=s[j]) j=p[j-1];
                if(s[i]==s[j]) j++;
                p[i]=j;
        }
        return p;
}

struct BIT {
        int n; vector<long long> bit;
        BIT(int n): n(n), bit(n+1,0) {}
        void add(int i,long long v){ for(++i;i<=n;i+=i&-i) bit[i]+=v; }
        long long sum(int i){ long long r=0; for(++i;i>0;i-=i&-i) r+=bit[i]; return r; }
};

vector<int> nge(n, -1);
stack<int> st;
for(int i=0;i<n;i++){
        while(!st.empty() && a[st.top()] < a[i]){
                nge[st.top()] = i;
                st.pop();
        }
        st.push(i);
}

queue<int> q;
for(int i=0;i<n;i++) if(indeg[i]==0) q.push(i);
vector<int> order;
while(!q.empty()){
        int u=q.front(); q.pop();
        order.push_back(u);
        for(int v: adj[u]){
                if(--indeg[v]==0) q.push(v);
        }
}

struct Seg {
        int n; vector<long long> t;
        Seg(int n): n(n), t(4*n, INF) {}
        void upd(int v,int tl,int tr,int pos,ll val){
                if(tl==tr){ t[v]=val; return; }
                int tm=(tl+tr)/2;
                if(pos<=tm) upd(v*2,tl,tm,pos,val);
                else upd(v*2+1,tm+1,tr,pos,val);
                t[v]=min(t[v*2],t[v*2+1]);
        }
        ll qry(int v,int tl,int tr,int l,int r){
                if(l>r) return INF;
                if(l==tl && r==tr) return t[v];
                int tm=(tl+tr)/2;
                return min(qry(v*2,tl,tm,l,min(r,tm)),
                                      qry(v*2+1,tm+1,tr,max(l,tm+1),r));
        }
};
OH ML

customer intelligence

02/09/2026 12:05

run identifier

• f6aa3094-627b-4b61-9aee-1d2afee4b1da

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9386F1 Score0.8636Precision • Recall0.8355 0.8937

recommendations

02/10/2026 01:51

run identifier

• e7a37bc3-b6f5-4889-8052-2cab9cab8dcd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999990R.M.S.E • M.A.E • M.S.E.0.0002 0.0000 0.0016

fraud detection

02/10/2026 07:10

run identifier

• f69a76bc-6034-4ecd-902b-85a11a0abb40

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9965F1 Score0.9759Precision • Recall0.9969 0.9557

🧬 · Loading data •

run identifier: 97f9ff6...

♥️ · Incubating Synthetic Data 🡥 •

run identifier: 97f9ff6...

📝 · New client data not found •

run identifier: 97f9ff6...

⌕ Checking for new training data •

run identifier: 97f9ff6...

▶ · Starting •

run identifier: 97f9ff6...

✔ · Completed •

run identifier: 3f1bb17...

💾 · Persisting model •

run identifier: 3f1bb17...

🌢 · Persisting metrics •

run identifier: 3f1bb17...

ƒ(x) · Evaluating •

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.91

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.91

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.91

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.89

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.93

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.91

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.88

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.89

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · L-BFGS Logistic Regression Binary · AUC (PR) 0.92

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.88

run identifier: 3f1bb17...

λ · Fast Forest Binary · AUC (PR) 0.88

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.88

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

λ · Fast Tree Binary · AUC (PR) 0.90

run identifier: 3f1bb17...

∑ · AutoML customer intelligence experiment in-progress •

run identifier: 3f1bb17...

⧉ · Training •

run identifier: 3f1bb17...

∞ · Building estimator chain •

run identifier: 3f1bb17...

⧉ · Training •

run identifier: 3f1bb17...

← ▣ → · Splitting data •

run identifier: 3f1bb17...

✨ · Segmenting •

run identifier: 3f1bb17...

⚡ · Data loaded •

run identifier: 3f1bb17...

🧬 · Loading data •

run identifier: 3f1bb17...

♥️ · Incubating Synthetic Data 🡥 •

run identifier: 3f1bb17...

📝 · New client data not found •

run identifier: 3f1bb17...

⌕ Checking for new training data •

run identifier: 3f1bb17...

▶ · Starting •

run identifier: 3f1bb17...

✔ · Completed •

run identifier: ccba9ab...

💾 · Persisting model •

run identifier: ccba9ab...

🌢 · Persisting metrics •

run identifier: ccba9ab...

ƒ(x) · Evaluating •

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9919

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9931

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9935

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9952

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9951

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9952

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9943

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9924

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9926

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9936

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9927

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

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λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

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λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

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λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

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λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

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λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9937

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9936

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9939

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9927

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9940

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9939

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9952

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9951

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9951

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9944

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9769

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9951

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9951

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9949

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9950

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9930

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9933

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9895

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9945

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9947

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9952

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9943

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9928

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9925

run identifier: ccba9ab...

λ · Fast Forest Binary · AUC (PR) 0.9948

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9943

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9928

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9941

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9918

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9946

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9944

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9943

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9939

run identifier: ccba9ab...

λ · Fast Tree Binary · AUC (PR) 0.9938

run identifier: ccba9ab...

02/11/2026 01:52

customer intelligence • run identifier • 3f1bb173-f313-4b8d-a9f2-4aba4ccc9b28

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9347F1 Score0.8520Precision • Recall0.8327 0.8722

02/11/2026 01:35

fraud detection • run identifier • ccba9abe-87b4-4852-bdb9-a63b1aa281a2

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9952F1 Score0.9673Precision • Recall0.9898 0.9457

02/11/2026 01:27

recommendations • run identifier • 0c9c4748-e739-4583-9d2b-675d56d57d26

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999919R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0046

02/11/2026 01:11

customer intelligence • run identifier • f32e8ec4-d5df-418b-b75c-5d9145d737a7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9369F1 Score0.8598Precision • Recall0.8296 0.8921

02/11/2026 12:54

fraud detection • run identifier • dccf8843-6310-47bb-b223-a79e0e638e13

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9737Precision • Recall1.0000 0.9487

02/11/2026 12:47

recommendations • run identifier • addbb795-9613-4fac-a8e2-9763ce8196c3

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999871R.M.S.E • M.A.E • M.S.E.0.0027 0.0000 0.0057

02/11/2026 12:30

customer intelligence • run identifier • cce0851f-e8f5-44a2-bcd0-ad9e64264154

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9379F1 Score0.8615Precision • Recall0.8325 0.8927

02/11/2026 12:13

fraud detection • run identifier • 615e2524-9d13-4a02-ac8b-bfe056ba51bd

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9961F1 Score0.9740Precision • Recall0.9964 0.9526

02/11/2026 12:06

recommendations • run identifier • b3a9dcc5-47f9-4506-9b83-afca473ebf7c

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999972R.M.S.E • M.A.E • M.S.E.0.0013 0.0000 0.0026

02/10/2026 11:49

customer intelligence • run identifier • c86a2b27-dffa-4230-83cf-7d3de152db18

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9350F1 Score0.8544Precision • Recall0.8312 0.8789

02/10/2026 11:32

fraud detection • run identifier • 68f81738-573e-4366-9e2d-843717f71923

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9729Precision • Recall0.9918 0.9546

02/10/2026 11:25

recommendations • run identifier • 3a1ce1ec-e7c8-4100-9ca4-0198576001ed

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998898R.M.S.E • M.A.E • M.S.E.0.0112 0.0003 0.0166

02/10/2026 11:08

customer intelligence • run identifier • aee032fb-575f-4a83-9bbe-455c05ffa121

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9352F1 Score0.8550Precision • Recall0.8256 0.8866

02/10/2026 10:51

fraud detection • run identifier • 7c8a0ac4-d551-468e-96c0-c70e60cd2e0a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9964F1 Score0.9749Precision • Recall1.0000 0.9510

02/10/2026 10:44

recommendations • run identifier • 846832b2-02b1-45f0-8fd0-d5ae6d5663fa

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999726R.M.S.E • M.A.E • M.S.E.0.0054 0.0001 0.0082

02/10/2026 10:27

customer intelligence • run identifier • 4eaeb8f4-26ee-470f-9df4-4eaac98561b0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9397F1 Score0.8620Precision • Recall0.8362 0.8894

02/10/2026 10:10

fraud detection • run identifier • 8e810ea9-3fb4-464e-9d77-56c12e74f538

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9970F1 Score0.9739Precision • Recall1.0000 0.9492

02/10/2026 10:03

recommendations • run identifier • ea9428da-acb0-45b5-8440-aeaae8c2a5ca

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999942R.M.S.E • M.A.E • M.S.E.0.0022 0.0000 0.0038

02/10/2026 09:46

customer intelligence • run identifier • d70f8bf1-eca1-43e4-a594-eda92006c73a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9365F1 Score0.8568Precision • Recall0.8355 0.8793

02/10/2026 09:29

fraud detection • run identifier • f1f6e5f0-22a4-43be-a466-3f6150cf9d4d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9944F1 Score0.9695Precision • Recall1.0000 0.9409

02/10/2026 09:22

recommendations • run identifier • 1e57dad6-501c-49d1-84ae-817ba5cc643a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999896R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0051

02/10/2026 09:05

customer intelligence • run identifier • 6137d1a3-2d39-4d49-94ab-345e076ebdbd

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9338F1 Score0.8564Precision • Recall0.8307 0.8837

02/10/2026 08:48

fraud detection • run identifier • 675f55d5-0360-4c57-9d9c-8bf4910a7321

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9680Precision • Recall0.9920 0.9451

02/10/2026 08:41

recommendations • run identifier • a21c4efa-8b13-4eff-b1f7-3c6da6e17245

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998892R.M.S.E • M.A.E • M.S.E.0.0084 0.0003 0.0166

02/10/2026 08:24

customer intelligence • run identifier • 8318b00d-f5fb-4d4b-a6fd-d16f503e5dad

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9352F1 Score0.8564Precision • Recall0.8313 0.8831

02/10/2026 08:08

fraud detection • run identifier • c7f627eb-faf9-4bc0-a812-3c19f2e30af0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9945F1 Score0.9713Precision • Recall1.0000 0.9443

02/10/2026 08:00

recommendations • run identifier • 91a67427-348b-4099-b608-f0f01a145253

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.997670R.M.S.E • M.A.E • M.S.E.0.0189 0.0006 0.0240

02/10/2026 07:43

customer intelligence • run identifier • 5720961d-46b1-4db1-b8fa-146016fb7b0f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9387F1 Score0.8591Precision • Recall0.8355 0.8840

02/10/2026 07:27

fraud detection • run identifier • 31b25d2a-6b0b-4d01-b23f-9738f3ef4fca

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9668Precision • Recall0.9866 0.9479

02/10/2026 07:19

recommendations • run identifier • 7aac5a80-a864-4b2d-a990-5d49987cf22e

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.991154R.M.S.E • M.A.E • M.S.E.0.0358 0.0022 0.0468

02/10/2026 07:02

customer intelligence • run identifier • d8aff86a-5de2-44f0-bdc4-e5ab34270b85

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9341F1 Score0.8576Precision • Recall0.8331 0.8836

02/10/2026 06:46

fraud detection • run identifier • 21dc30a7-650e-4b73-b9a8-692c852d6847

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9740Precision • Recall0.9937 0.9550

02/10/2026 06:38

recommendations • run identifier • f35cea26-9a8a-424a-a9c8-71c8ab1f7f8a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999875R.M.S.E • M.A.E • M.S.E.0.0018 0.0000 0.0056

02/10/2026 06:21

customer intelligence • run identifier • 6af00101-7489-4dba-b188-7978750ee7f8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9373F1 Score0.8607Precision • Recall0.8362 0.8866

02/10/2026 06:05

fraud detection • run identifier • 1aca6a8b-0b6b-4aef-bfdd-1b7ebd12f0e8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9961F1 Score0.9739Precision • Recall0.9989 0.9500

02/10/2026 05:57

recommendations • run identifier • 1d44a237-7fed-4a11-aa28-e9c71e47b57d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999853R.M.S.E • M.A.E • M.S.E.0.0035 0.0000 0.0061

02/10/2026 05:40

customer intelligence • run identifier • dd151bb9-3b77-48ee-90df-b92182c873fc

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9370F1 Score0.8604Precision • Recall0.8365 0.8857

02/10/2026 05:24

fraud detection • run identifier • bb38cc53-3017-40d0-b1f0-a665ba0f2dbb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9940F1 Score0.9646Precision • Recall0.9949 0.9361

02/10/2026 05:16

recommendations • run identifier • 7b0ed6aa-8a31-4dab-b3ba-9803b8481fe5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999912R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0047

02/10/2026 04:59

customer intelligence • run identifier • 2cf1fafa-0cee-46f3-98f2-40b5c84ec65c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9361F1 Score0.8574Precision • Recall0.8320 0.8843

02/10/2026 04:43

fraud detection • run identifier • ec4da00d-8fd1-4f69-b499-b78c209a774e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9726Precision • Recall1.0000 0.9466

02/10/2026 04:35

recommendations • run identifier • 158ffd72-6566-4490-965f-4c294f0701ad

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999928R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0042

02/10/2026 04:18

customer intelligence • run identifier • e43e6e31-c50d-42ec-8e10-3e66dbd4700b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9373F1 Score0.8589Precision • Recall0.8402 0.8785

02/10/2026 04:02

fraud detection • run identifier • 80c9ec5e-acfe-469d-bd9c-973d1f7abff1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9722Precision • Recall0.9966 0.9490

02/10/2026 03:54

recommendations • run identifier • 43ee8cfd-9592-4f43-9fbf-6b42d310b5e6

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999844R.M.S.E • M.A.E • M.S.E.0.0030 0.0000 0.0063

02/10/2026 03:37

customer intelligence • run identifier • cafdddb0-8d88-40e0-b058-8f35d61af235

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9332F1 Score0.8549Precision • Recall0.8291 0.8823

02/10/2026 03:21

fraud detection • run identifier • a3c68194-e5dd-4c70-b5f9-11f15a904d33

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9950F1 Score0.9690Precision • Recall1.0000 0.9399

02/10/2026 03:13

recommendations • run identifier • 25647661-ce88-400d-a044-338909ceca13

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999908R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0048

02/10/2026 02:56

customer intelligence • run identifier • f8c52b23-90b8-4d20-9253-49257168ea6f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9363F1 Score0.8584Precision • Recall0.8368 0.8813

02/10/2026 02:40

fraud detection • run identifier • 7b3a1505-2d1f-4d85-97a1-f3ff72760a55

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9956F1 Score0.9713Precision • Recall1.0000 0.9442

02/10/2026 02:32

recommendations • run identifier • 05162d0b-33a0-4d9c-b820-8c8b7a88b572

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999427R.M.S.E • M.A.E • M.S.E.0.0079 0.0001 0.0120

02/10/2026 02:15

customer intelligence • run identifier • e6702511-4165-4327-a330-564dc52d9974

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9376F1 Score0.8611Precision • Recall0.8327 0.8914

02/10/2026 01:59

fraud detection • run identifier • cf3953ba-7532-47b7-9fac-6b3bea0f1ea7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9954F1 Score0.9731Precision • Recall1.0000 0.9477

02/10/2026 01:51

recommendations • run identifier • e7a37bc3-b6f5-4889-8052-2cab9cab8dcd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999990R.M.S.E • M.A.E • M.S.E.0.0002 0.0000 0.0016

02/10/2026 01:35

customer intelligence • run identifier • c735e5ef-18c4-4d4d-818c-5d63118000f8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9347F1 Score0.8587Precision • Recall0.8338 0.8851

02/10/2026 01:18

fraud detection • run identifier • 061a473d-6db9-4473-9d8d-592dd55439d8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9950F1 Score0.9653Precision • Recall1.0000 0.9330

02/10/2026 01:10

recommendations • run identifier • 5cc416b9-e647-4aab-8362-d4c692d3e8ce

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999922R.M.S.E • M.A.E • M.S.E.0.0020 0.0000 0.0044

02/10/2026 12:54

customer intelligence • run identifier • 252a8bfb-7ba6-4e19-b61c-3ca4db6c94ea

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9361F1 Score0.8603Precision • Recall0.8339 0.8885

02/10/2026 12:37

fraud detection • run identifier • ece85451-23cd-4d25-953e-6f3103aa384b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9698Precision • Recall0.9994 0.9419

02/10/2026 12:29

recommendations • run identifier • 9b9a3136-ab26-4124-a6da-97ee3c45a8d7

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999873R.M.S.E • M.A.E • M.S.E.0.0020 0.0000 0.0056

02/10/2026 12:13

customer intelligence • run identifier • 5c185b81-0026-4354-a8e3-e75f415a715c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9383F1 Score0.8620Precision • Recall0.8358 0.8898

02/10/2026 11:56

fraud detection • run identifier • 741bfc29-6368-4e4f-a953-c3fe239d543f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9956F1 Score0.9703Precision • Recall1.0000 0.9423

02/10/2026 11:48

recommendations • run identifier • 665ed22c-908d-46db-b5f9-dad23ebea063

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999880R.M.S.E • M.A.E • M.S.E.0.0024 0.0000 0.0055

02/10/2026 11:32

customer intelligence • run identifier • 1fd7dab4-397a-41ff-8f31-8d565587465f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9356F1 Score0.8600Precision • Recall0.8374 0.8838

02/10/2026 11:15

fraud detection • run identifier • 56aeeb50-cc8f-43c1-9e2e-755dadea9bc9

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9745Precision • Recall1.0000 0.9502

02/10/2026 11:07

recommendations • run identifier • b4132c1b-4fe6-42b9-8e69-28be8067dfd3

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999831R.M.S.E • M.A.E • M.S.E.0.0034 0.0000 0.0065

02/10/2026 10:51

customer intelligence • run identifier • 346e0f26-370f-446c-b774-cf533cf4b8bf

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9323F1 Score0.8552Precision • Recall0.8289 0.8833

02/10/2026 10:34

fraud detection • run identifier • 6ead8004-760a-416e-ae41-cebe6b24a0be

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9732Precision • Recall1.0000 0.9478

02/10/2026 10:27

recommendations • run identifier • d6a59541-fe8d-4d81-a9b8-112179ef3d71

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998084R.M.S.E • M.A.E • M.S.E.0.0148 0.0005 0.0219

02/10/2026 10:10

customer intelligence • run identifier • 330c0259-4f83-4fb3-a765-ad28e9d91fa0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9335F1 Score0.8562Precision • Recall0.8334 0.8802

02/10/2026 09:53

fraud detection • run identifier • e48536a5-dd11-45ca-bb91-e2a1155e09f3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9955F1 Score0.9694Precision • Recall0.9982 0.9422

02/10/2026 09:46

recommendations • run identifier • 056e4027-8866-4b7a-8d01-fd488f87044d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998940R.M.S.E • M.A.E • M.S.E.0.0114 0.0003 0.0163

02/10/2026 09:29

customer intelligence • run identifier • 69d77cf3-a766-453c-8ab9-e0cbb13d6789

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9341F1 Score0.8584Precision • Recall0.8317 0.8869

02/10/2026 09:12

fraud detection • run identifier • e0e65571-01a7-4099-aeba-d46cec552b41

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9951F1 Score0.9696Precision • Recall0.9955 0.9450

02/10/2026 09:05

recommendations • run identifier • 20bd1ae3-4fcc-45f3-bb50-10ceb5cb60ad

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999791R.M.S.E • M.A.E • M.S.E.0.0047 0.0001 0.0073

02/10/2026 08:48

customer intelligence • run identifier • adfbf34b-7c2a-46bf-a4df-7015f4f2f0b7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9377F1 Score0.8634Precision • Recall0.8366 0.8920

02/10/2026 08:31

fraud detection • run identifier • d3d5d1fc-99ae-4f2a-b1d1-21187b61583d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9973F1 Score0.9748Precision • Recall0.9896 0.9603

02/10/2026 08:24

recommendations • run identifier • a1744a30-65e4-4e5d-95a2-4b7320c6b541

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.997788R.M.S.E • M.A.E • M.S.E.0.0160 0.0006 0.0237

02/10/2026 08:07

customer intelligence • run identifier • c437f10c-b659-44bb-be40-58df61e21573

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8603Precision • Recall0.8358 0.8863

02/10/2026 07:51

fraud detection • run identifier • f00a5699-43b5-460e-b302-cfd6495bda86

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9716Precision • Recall1.0000 0.9447

02/10/2026 07:43

recommendations • run identifier • 9102fe43-728d-43d6-ba81-553ee70b7c4f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.988934R.M.S.E • M.A.E • M.S.E.0.0429 0.0028 0.0530

02/10/2026 07:26

customer intelligence • run identifier • b71ece88-eda2-427d-a988-023b9538770a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9360F1 Score0.8601Precision • Recall0.8331 0.8889

02/10/2026 07:10

fraud detection • run identifier • f69a76bc-6034-4ecd-902b-85a11a0abb40

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9965F1 Score0.9759Precision • Recall0.9969 0.9557

02/10/2026 07:02

recommendations • run identifier • a9b87264-578e-47e8-840a-ad3227993b4f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999831R.M.S.E • M.A.E • M.S.E.0.0028 0.0000 0.0065

02/10/2026 06:45

customer intelligence • run identifier • a14605da-07af-45fe-95dd-c768cb3e4376

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9376F1 Score0.8594Precision • Recall0.8360 0.8841

02/10/2026 06:29

fraud detection • run identifier • 5eeb5367-67c7-43a9-bd62-81ecb2167069

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9963F1 Score0.9745Precision • Recall0.9973 0.9527

02/10/2026 06:21

recommendations • run identifier • 86ed4f48-88f0-4ddc-9234-f868b162bae9

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999912R.M.S.E • M.A.E • M.S.E.0.0029 0.0000 0.0047

02/10/2026 06:05

customer intelligence • run identifier • d7bc2f3b-e35b-47e8-80d0-991d95cc2a11

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9371F1 Score0.8614Precision • Recall0.8369 0.8874

02/10/2026 05:48

fraud detection • run identifier • 6ca32b00-5b18-4cb1-a6e7-3461a8ae40e1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9715Precision • Recall0.9973 0.9469

02/10/2026 05:40

recommendations • run identifier • 1dfaa77d-95ab-4365-9fc3-7a435994efe4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999910R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0048

02/10/2026 05:24

customer intelligence • run identifier • 3426e7b0-5a80-4431-a0c3-52d1b9fde4f4

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9385F1 Score0.8593Precision • Recall0.8305 0.8903

02/10/2026 05:07

fraud detection • run identifier • 76d9e86e-0292-4fc2-b274-b7268ef1c9de

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9966F1 Score0.9715Precision • Recall0.9953 0.9488

02/10/2026 04:59

recommendations • run identifier • a2ebd3f6-bcf7-478b-82ab-52f5fcc0730d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999350R.M.S.E • M.A.E • M.S.E.0.0078 0.0002 0.0128

02/10/2026 04:43

customer intelligence • run identifier • 0595fe24-9cb8-4d7e-b981-3d4cf2423582

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9370F1 Score0.8597Precision • Recall0.8379 0.8827

02/10/2026 04:24

fraud detection • run identifier • e1f59baf-270e-47be-a19d-169ac176bd30

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9735Precision • Recall1.0000 0.9484

02/10/2026 04:16

recommendations • run identifier • 37b72618-291e-4227-aa70-39a0bfacb6d7

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999947R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0037

02/10/2026 04:00

customer intelligence • run identifier • b6b92681-6c80-433e-bc16-3600a9d5aeb4

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9384F1 Score0.8607Precision • Recall0.8340 0.8891

02/10/2026 02:50

recommendations • run identifier • b42f9b61-36ab-429a-8733-f8ff902dd2f5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999776R.M.S.E • M.A.E • M.S.E.0.0050 0.0001 0.0076

02/10/2026 02:33

customer intelligence • run identifier • c461c685-e2fa-426a-8337-1dd2971ff15c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9370F1 Score0.8572Precision • Recall0.8339 0.8818

02/10/2026 02:17

fraud detection • run identifier • 915fab0c-b106-4ca4-aff8-af460f0356a0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9959F1 Score0.9747Precision • Recall0.9983 0.9522

02/10/2026 02:09

recommendations • run identifier • 35669cca-ac86-4da6-8b56-1557aacbcdf2

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998132R.M.S.E • M.A.E • M.S.E.0.0142 0.0005 0.0219

02/10/2026 01:52

customer intelligence • run identifier • 098ad7f8-010c-4aa1-871c-7b3e80412509

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9377F1 Score0.8608Precision • Recall0.8365 0.8867

02/10/2026 01:36

fraud detection • run identifier • ff130323-aed0-472d-b64f-7aff6903e8cb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9972F1 Score0.9746Precision • Recall0.9987 0.9516

02/10/2026 01:28

recommendations • run identifier • 433c4d45-c47d-4fa7-a6e9-cef89863b70f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999926R.M.S.E • M.A.E • M.S.E.0.0025 0.0000 0.0044

02/10/2026 01:11

customer intelligence • run identifier • d02aeec4-4617-4a65-9faa-e2fa328d80a9

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9366F1 Score0.8595Precision • Recall0.8357 0.8847

02/10/2026 12:55

fraud detection • run identifier • 8d201b83-49be-4608-902c-2ad374c4d1c6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9746Precision • Recall1.0000 0.9504

02/10/2026 12:47

recommendations • run identifier • b7224d67-a30e-4707-a495-9e6efec9514c

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999889R.M.S.E • M.A.E • M.S.E.0.0023 0.0000 0.0053

02/10/2026 12:31

customer intelligence • run identifier • 01e9aedc-fc0c-45ca-87b8-ab502e146645

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9343F1 Score0.8549Precision • Recall0.8286 0.8829

02/10/2026 12:14

fraud detection • run identifier • c6a1c28e-e134-4bfc-b80e-4260dd179bac

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9725Precision • Recall1.0000 0.9464

02/10/2026 12:06

recommendations • run identifier • 6055b72f-a235-4102-a2e7-8d12640650d5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999247R.M.S.E • M.A.E • M.S.E.0.0080 0.0002 0.0137

02/09/2026 11:50

customer intelligence • run identifier • cf39f031-3391-47c5-808a-d903d38cc387

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9379F1 Score0.8608Precision • Recall0.8346 0.8888

02/09/2026 11:33

fraud detection • run identifier • 049a9581-3e16-4452-a874-500f7ea2c3bd

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9946F1 Score0.9715Precision • Recall1.0000 0.9447

02/09/2026 11:25

recommendations • run identifier • 9e9efa2c-daaa-4230-b944-69be19e936e3

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.997895R.M.S.E • M.A.E • M.S.E.0.0127 0.0005 0.0228

02/09/2026 11:09

customer intelligence • run identifier • 5bb581c9-8e16-417d-ac94-8804fc552886

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8628Precision • Recall0.8376 0.8896

02/09/2026 10:52

fraud detection • run identifier • 625d01b8-e5b7-4813-881f-46c6ce8ce754

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9682Precision • Recall0.9899 0.9474

02/09/2026 10:44

recommendations • run identifier • 6d251926-ed93-493c-a786-5d033448d534

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999842R.M.S.E • M.A.E • M.S.E.0.0036 0.0000 0.0062

02/09/2026 10:28

customer intelligence • run identifier • 2768461f-5f8c-4027-b2b8-907c5a43f413

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9381F1 Score0.8629Precision • Recall0.8373 0.8901

02/09/2026 10:11

fraud detection • run identifier • 66a75965-a81a-4183-9387-70ba7c14a03b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9732Precision • Recall1.0000 0.9478

02/09/2026 10:03

recommendations • run identifier • 7222e752-82ec-43da-9782-328c5b39b6e4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999680R.M.S.E • M.A.E • M.S.E.0.0047 0.0001 0.0089

02/09/2026 09:47

customer intelligence • run identifier • a5569131-4158-4e29-afa2-5bf81cdee408

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9384F1 Score0.8589Precision • Recall0.8369 0.8822

02/09/2026 09:30

fraud detection • run identifier • fd046cf5-6212-46a2-8b71-6067a2759e4c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9949F1 Score0.9682Precision • Recall0.9983 0.9399

02/09/2026 09:22

recommendations • run identifier • d4cdd6d0-b85d-47e5-93f4-92910c6d58c5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999181R.M.S.E • M.A.E • M.S.E.0.0100 0.0002 0.0143

02/09/2026 09:06

customer intelligence • run identifier • 626ea060-bd5c-4149-9f31-4fda946e4683

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9391F1 Score0.8607Precision • Recall0.8364 0.8866

02/09/2026 08:49

fraud detection • run identifier • 71b7f3de-533b-47b7-a0a8-d56e567ac0c5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9728Precision • Recall0.9976 0.9491

02/09/2026 08:42

recommendations • run identifier • b5c7c8a3-1840-49e9-9bb1-90409ed3313c

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999901R.M.S.E • M.A.E • M.S.E.0.0024 0.0000 0.0050

02/09/2026 08:25

customer intelligence • run identifier • 449de92d-7c99-441e-b4e7-1c925fbb62a8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9380F1 Score0.8617Precision • Recall0.8387 0.8860

02/09/2026 08:06

fraud detection • run identifier • 2d80cc8c-9997-4758-a8b3-cae4e3ad5cec

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9967F1 Score0.9730Precision • Recall0.9991 0.9482

02/09/2026 07:59

recommendations • run identifier • 0b1850d3-4b34-4127-8249-863e0c1ffe2f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999817R.M.S.E • M.A.E • M.S.E.0.0045 0.0000 0.0067

02/09/2026 07:42

customer intelligence • run identifier • 7b9d9b50-2f0f-46d7-ad03-d4e16a257431

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9360F1 Score0.8586Precision • Recall0.8322 0.8867

02/09/2026 07:12

recommendations • run identifier • 4e9aaf38-3c88-43cf-877c-bc0fed28f40f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.996405R.M.S.E • M.A.E • M.S.E.0.0198 0.0009 0.0299

02/09/2026 06:56

customer intelligence • run identifier • 482917bf-7ad1-4138-9397-6414a5a5c29f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9343F1 Score0.8575Precision • Recall0.8364 0.8797

02/09/2026 06:39

fraud detection • run identifier • e1456706-ed9b-42a0-87da-5f80a59e3196

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9955F1 Score0.9708Precision • Recall0.9963 0.9466

02/09/2026 06:31

recommendations • run identifier • a5aa43b6-3b49-4b16-82f6-be985ad014e0

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.996206R.M.S.E • M.A.E • M.S.E.0.0229 0.0009 0.0308

02/09/2026 06:15

customer intelligence • run identifier • 34831ea3-d7ef-40a2-ae4c-cc2bb66d0ccf

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9352F1 Score0.8578Precision • Recall0.8289 0.8888

02/09/2026 05:58

fraud detection • run identifier • 9c1c9404-dbde-4c03-949f-a09c38b4c2d1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9969F1 Score0.9733Precision • Recall1.0000 0.9479

02/09/2026 05:50

recommendations • run identifier • 82cbb688-2521-4bf8-a31c-403e370f7023

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999901R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0050

02/09/2026 05:33

customer intelligence • run identifier • 7c67dd0d-e3e6-4546-8ad6-bffb7e800fce

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9373F1 Score0.8622Precision • Recall0.8351 0.8911

02/09/2026 05:17

fraud detection • run identifier • 24aeb711-3c2c-4035-af5f-129010018494

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9750Precision • Recall1.0000 0.9513

02/09/2026 05:09

recommendations • run identifier • c16f0bae-7eae-46cd-a472-e5f3e3ce22f5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999944R.M.S.E • M.A.E • M.S.E.0.0021 0.0000 0.0038

02/09/2026 04:52

customer intelligence • run identifier • 66770573-2f1e-4d96-ae6c-4bd746e9b164

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9347F1 Score0.8547Precision • Recall0.8341 0.8762

02/09/2026 04:36

fraud detection • run identifier • 77cd7730-8e11-48e9-ac1f-bc8de0d7da41

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9682Precision • Recall1.0000 0.9384

02/09/2026 04:28

recommendations • run identifier • 28e5c991-45cd-417a-9f77-475c6aaee45d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999907R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0048

02/09/2026 04:11

customer intelligence • run identifier • 19b6120f-58c1-4b92-917b-e06c23dd9057

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9342F1 Score0.8576Precision • Recall0.8344 0.8822

02/09/2026 03:54

fraud detection • run identifier • 0395f4dd-bfa9-4fae-b95a-4eca73fa1acb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9961F1 Score0.9684Precision • Recall0.9925 0.9455

02/09/2026 03:47

recommendations • run identifier • 70911993-b83f-469f-82b4-8e2449af3d61

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999903R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0049

02/09/2026 03:30

customer intelligence • run identifier • 653b3b4b-2441-4ade-8cb0-ad3fc54fce31

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9359F1 Score0.8595Precision • Recall0.8305 0.8905

02/09/2026 03:13

fraud detection • run identifier • c56719c8-5253-4da4-ba79-4d3307d62097

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9956F1 Score0.9706Precision • Recall1.0000 0.9429

02/09/2026 03:06

recommendations • run identifier • bccce0e2-b79d-459c-8521-62478c31b5bf

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999980R.M.S.E • M.A.E • M.S.E.0.0012 0.0000 0.0022

02/09/2026 02:49

customer intelligence • run identifier • a2185948-0d0e-4d25-a577-4eb2aa1dc187

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9350F1 Score0.8564Precision • Recall0.8338 0.8804

02/09/2026 02:32

fraud detection • run identifier • f85493fb-d956-4987-a41a-eed6edb8e728

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9687Precision • Recall1.0000 0.9393

02/09/2026 02:25

recommendations • run identifier • 602b2593-82a4-4ed6-875c-dc9fc87ad2f7

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.975990R.M.S.E • M.A.E • M.S.E.0.0591 0.0060 0.0776

02/09/2026 02:08

customer intelligence • run identifier • c158b50d-9f08-4e47-952d-0d78c4b63b88

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9367F1 Score0.8592Precision • Recall0.8321 0.8880

02/09/2026 01:51

fraud detection • run identifier • 844354eb-f258-42ad-b2de-57b959c486e2

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9733Precision • Recall1.0000 0.9480

02/09/2026 01:44

recommendations • run identifier • d3702f27-b100-4cb9-a623-33c564a5973b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999926R.M.S.E • M.A.E • M.S.E.0.0021 0.0000 0.0043

02/09/2026 01:27

customer intelligence • run identifier • b63e5d53-b572-4fde-a93d-69b738673382

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9384F1 Score0.8609Precision • Recall0.8333 0.8905

02/09/2026 01:10

fraud detection • run identifier • 393ef95a-3c3e-41e5-a1c8-335ff6f6f8ad

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9964F1 Score0.9727Precision • Recall0.9983 0.9484

02/09/2026 01:03

recommendations • run identifier • 978556a4-171f-40e2-875b-cbc4b60e4c00

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999412R.M.S.E • M.A.E • M.S.E.0.0073 0.0001 0.0122

02/09/2026 12:46

customer intelligence • run identifier • 64926134-b685-43c1-9cf8-e029ffbf3a81

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9374F1 Score0.8606Precision • Recall0.8320 0.8912

02/09/2026 12:29

fraud detection • run identifier • c8fded9d-f5ac-452e-8846-6bd2043e9e16

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9733Precision • Recall1.0000 0.9481

02/09/2026 12:22

recommendations • run identifier • f2affeb2-90f3-4325-bbd8-617dc65287ed

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999887R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0053

02/09/2026 12:05

customer intelligence • run identifier • f6aa3094-627b-4b61-9aee-1d2afee4b1da

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9386F1 Score0.8636Precision • Recall0.8355 0.8937

02/09/2026 11:48

fraud detection • run identifier • 5cecf621-9db9-4c9e-8729-fcfb56d7d1d4

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9948F1 Score0.9658Precision • Recall1.0000 0.9338

02/09/2026 11:41

recommendations • run identifier • 230f09f2-80d5-4885-ad23-05899362ae81

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999895R.M.S.E • M.A.E • M.S.E.0.0031 0.0000 0.0051

02/09/2026 11:24

customer intelligence • run identifier • 4d0769d5-55ce-4ae3-9a70-4d00158c941f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9359F1 Score0.8569Precision • Recall0.8307 0.8849

02/09/2026 11:07

fraud detection • run identifier • 9930e74a-1184-4757-8c29-5ce797441b79

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9702Precision • Recall0.9944 0.9472

02/09/2026 11:00

recommendations • run identifier • 369a465b-031a-463a-8d92-6bcca7423a87

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999723R.M.S.E • M.A.E • M.S.E.0.0052 0.0001 0.0084

02/09/2026 10:43

customer intelligence • run identifier • 845ec140-00e1-40f7-ba15-48f22da100f1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9374F1 Score0.8608Precision • Recall0.8376 0.8852

02/09/2026 10:26

fraud detection • run identifier • cc2a72b5-63b5-4693-8c92-45cda9071280

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9953F1 Score0.9685Precision • Recall0.9976 0.9411

02/09/2026 10:19

recommendations • run identifier • 8bb1d451-1105-4bd7-83cc-88061aa76896

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999791R.M.S.E • M.A.E • M.S.E.0.0042 0.0001 0.0073

02/09/2026 10:02

customer intelligence • run identifier • a6a119c8-8557-40b6-bed0-d2ff0c07f387

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9350F1 Score0.8582Precision • Recall0.8300 0.8883

02/09/2026 09:45

fraud detection • run identifier • aaf9726e-a2c2-49a2-80fb-ab50b2aa41b8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9950F1 Score0.9686Precision • Recall1.0000 0.9390

02/09/2026 09:38

recommendations • run identifier • e58392d7-f8b9-4799-89f9-19514f6e29cf

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999896R.M.S.E • M.A.E • M.S.E.0.0018 0.0000 0.0051

02/09/2026 09:21

customer intelligence • run identifier • f0d564c4-fbbe-4963-b5cf-ef2cc16fa671

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8599Precision • Recall0.8349 0.8864

02/09/2026 09:02

fraud detection • run identifier • acf976b1-9431-4866-8167-6dc6a9597fb0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9706Precision • Recall1.0000 0.9430

02/09/2026 08:55

recommendations • run identifier • 4bcd7a6b-216e-47e4-b23b-1d607fc440d0

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998857R.M.S.E • M.A.E • M.S.E.0.0120 0.0003 0.0171

02/09/2026 08:38

customer intelligence • run identifier • 2d865cc0-1b03-440c-932b-24de511fb562

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9373F1 Score0.8589Precision • Recall0.8364 0.8826

02/09/2026 08:17

recommendations • run identifier • 8c7f34dc-7679-4686-b999-50fd8f06d5cb

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)LightGBM RegressionR²0.946009R.M.S.E • M.A.E • M.S.E.0.0840 0.0137 0.1170

02/09/2026 08:10

customer intelligence • run identifier • 4a3e42cf-111d-4e7d-8d0d-2de1f590f0d8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9374F1 Score0.8603Precision • Recall0.8337 0.8888

02/09/2026 08:03

customer intelligence • run identifier • 6abd213f-006e-4a87-ac7f-3af51bbe2be7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9381F1 Score0.8579Precision • Recall0.8316 0.8858

02/09/2026 07:54

fraud detection • run identifier • 098e7cc4-bd07-4545-b6da-522502bd9f36

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9679Precision • Recall0.9982 0.9393

02/09/2026 07:46

recommendations • run identifier • 9437166c-1cb7-48d1-b82f-7f2370719a76

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.972327R.M.S.E • M.A.E • M.S.E.0.0673 0.0070 0.0837

02/09/2026 07:29

customer intelligence • run identifier • be12789a-1aab-4a80-9c46-52c21c77f99f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9371F1 Score0.8620Precision • Recall0.8360 0.8897

02/09/2026 07:10

fraud detection • run identifier • afb317a3-3d98-4e80-b911-83e028cf93e6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9934F1 Score0.9632Precision • Recall1.0000 0.9290

02/09/2026 07:03

recommendations • run identifier • 46145435-106a-4ab8-bf0b-85b2297f90b4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998515R.M.S.E • M.A.E • M.S.E.0.0135 0.0004 0.0194

02/09/2026 06:46

customer intelligence • run identifier • f8221699-df23-49d8-a34d-81f6402fdff5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9373F1 Score0.8607Precision • Recall0.8350 0.8880

02/09/2026 06:19

recommendations • run identifier • fe2147fd-2511-4416-b3a6-54036d7f07cd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998198R.M.S.E • M.A.E • M.S.E.0.0148 0.0005 0.0214

02/09/2026 06:03

customer intelligence • run identifier • c169695f-7206-4b71-82fe-427a3f03f9f8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9362F1 Score0.8578Precision • Recall0.8327 0.8844

02/09/2026 05:44

fraud detection • run identifier • 6c318548-79bc-42e8-b025-7bcc074ac9c1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9715Precision • Recall1.0000 0.9446

02/09/2026 05:36

recommendations • run identifier • e32e40da-4d48-474e-8697-cfcab1d31d9e

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999856R.M.S.E • M.A.E • M.S.E.0.0023 0.0000 0.0061

02/09/2026 05:20

customer intelligence • run identifier • 9477d96e-1179-427a-bc06-0887355e0d7b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9353F1 Score0.8567Precision • Recall0.8287 0.8865

02/09/2026 04:56

recommendations • run identifier • c388a0f0-4ff2-4caf-a07d-02b5e27b2270

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999878R.M.S.E • M.A.E • M.S.E.0.0026 0.0000 0.0056

02/09/2026 04:39

customer intelligence • run identifier • 45b2a7c9-5e36-4b4a-bd07-259a57dd0dd9

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9368F1 Score0.8586Precision • Recall0.8288 0.8906

02/09/2026 04:23

fraud detection • run identifier • 4ae4b201-77f2-48ad-bef4-775f91a3026d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9955F1 Score0.9681Precision • Recall0.9930 0.9444

02/09/2026 04:15

recommendations • run identifier • f2f3739f-e0bc-4955-8b04-83f4a8acc311

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999854R.M.S.E • M.A.E • M.S.E.0.0033 0.0000 0.0061

02/09/2026 03:58

customer intelligence • run identifier • 3276c5e2-3fa3-4e26-b2c4-7a5cebf1da36

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9318F1 Score0.8534Precision • Recall0.8226 0.8866

02/09/2026 03:42

fraud detection • run identifier • 02d63e7f-1d42-4ed5-813f-8e198a4af182

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9728Precision • Recall1.0000 0.9471

02/09/2026 03:34

recommendations • run identifier • 437250e9-b5dd-43ad-8e36-ee8e14529336

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999892R.M.S.E • M.A.E • M.S.E.0.0024 0.0000 0.0052