./readyDOS/ 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));
        }
};;
ReadyDOS
  • automationProductskeyboard_arrow_down

Ranked Models

Customer Intelligence

06/01/2026 04:23

run identifier

• bc11bc1c-7f4a-4c31-b768-e81c45fecca3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8613Precision • Recall0.8370 0.8871

Recommendations

06/01/2026 03:58

run identifier

• 8248105b-00b7-42dc-a41a-c851f9737db8

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999987R.M.S.E • M.A.E • M.S.E.0.0004 0.0000 0.0018

Fraud Detection

06/01/2026 08:14

run identifier

• 50755609-a809-411c-a0f9-b04ccf4c2a98

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9975F1 Score0.9780Precision • Recall0.9972 0.9596
Live Logs

🧬 Loading data ﹙≈ 3-8 mins; standby﹚

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🌱 Generating stochastic, realistic synthetic users and activity events

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📝 New client data not found

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⌕ Checking for new training data

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▶ Starting

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✔ Completed

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💾 Persisting model

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🌢 Persisting metrics

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λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9945

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9941

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9946

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9951

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9947

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9950

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9957

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9953

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9956

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9945

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9944

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9945

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9950

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9947

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9952

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9944

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9945

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9952

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9955

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9949

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9940

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9952

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9954

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9950

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9944

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9953

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9949

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9952

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9949

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9948

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9935

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9938

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9941

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9951

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9926

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9949

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9925

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9933

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9942

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9942

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9925

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9935

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9925

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9941

run identifier: 782a248...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9943

run identifier: 782a248...

Workflow History

06/02/2026 12:30

Fraud Detection • run identifier • 782a248f-6873-40fc-ad34-789b36806936

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9748Precision • Recall0.9963 0.9542

06/02/2026 12:22

Recommendations • run identifier • 3e7d5369-7f8c-4aba-bfa0-18ba745889c4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999984R.M.S.E • M.A.E • M.S.E.0.0005 0.0000 0.0021

06/02/2026 12:06

Customer Intelligence • run identifier • f7ca0a54-476f-44ec-9cc9-a0b0c292d7b2

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9342F1 Score0.8599Precision • Recall0.8210 0.9028

06/02/2026 11:49

Fraud Detection • run identifier • d4b14990-e92a-40c4-a00a-11d38975ee19

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9965F1 Score0.9741Precision • Recall1.0000 0.9496

06/02/2026 11:41

Recommendations • run identifier • 5d6cfbdf-705f-44be-9008-dcda68fc7d0e

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999197R.M.S.E • M.A.E • M.S.E.0.0087 0.0002 0.0147

06/02/2026 11:25

Customer Intelligence • run identifier • a37a9c7d-4941-4d5c-8d65-91f18306b121

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9331F1 Score0.8557Precision • Recall0.8273 0.8860

06/02/2026 11:08

Fraud Detection • run identifier • af7f3faa-9f3c-43a8-8362-ed766646a9bb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9964F1 Score0.9759Precision • Recall1.0000 0.9530

06/02/2026 11:01

Recommendations • run identifier • 1d680610-4d7d-428f-8c50-83dab6067759

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998433R.M.S.E • M.A.E • M.S.E.0.0138 0.0004 0.0204

06/02/2026 10:44

Customer Intelligence • run identifier • fe03f9fc-f191-4f42-8262-2f4140bc6857

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9380F1 Score0.8612Precision • Recall0.8351 0.8890

06/02/2026 10:27

Fraud Detection • run identifier • c240a3b4-98b5-463f-b3f7-1bdd13a7486b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9697Precision • Recall0.9958 0.9449

06/02/2026 10:20

Recommendations • run identifier • 5d02647a-834a-4a0a-81f7-bd2271bc8be1

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999824R.M.S.E • M.A.E • M.S.E.0.0037 0.0000 0.0068

06/02/2026 10:03

Customer Intelligence • run identifier • e2287ea1-0321-498f-88c6-693d474468a6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9375F1 Score0.8607Precision • Recall0.8360 0.8869

06/02/2026 09:46

Fraud Detection • run identifier • 9ef36194-79e3-49b9-8ad9-341e181883e7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9948F1 Score0.9713Precision • Recall0.9952 0.9484

06/02/2026 09:39

Recommendations • run identifier • d678abef-b0c8-4d7a-ae9e-0d05c0a57a9b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.988606R.M.S.E • M.A.E • M.S.E.0.0365 0.0030 0.0549

06/02/2026 09:22

Customer Intelligence • run identifier • 60df5805-2292-4759-bcd2-e29ee79125c8

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9351F1 Score0.8583Precision • Recall0.8364 0.8814

06/02/2026 09:05

Fraud Detection • run identifier • 4213789c-7120-481d-837c-bda761877f7d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9688Precision • Recall0.9940 0.9449

06/02/2026 08:58

Recommendations • run identifier • f3a8492a-8fed-4ff4-ab98-f6304a319a34

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999965R.M.S.E • M.A.E • M.S.E.0.0013 0.0000 0.0031

06/02/2026 08:41

Customer Intelligence • run identifier • e7b3318d-86a6-4aae-b918-4faaf0605b43

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9371F1 Score0.8594Precision • Recall0.8335 0.8870

06/02/2026 08:22

Fraud Detection • run identifier • 43f1ad7a-0d49-46b4-a55f-2bad03236999

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9953F1 Score0.9672Precision • Recall0.9940 0.9418

06/02/2026 08:15

Recommendations • run identifier • aa625946-8bfb-4449-959f-2669f7f8a7bd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998995R.M.S.E • M.A.E • M.S.E.0.0115 0.0003 0.0164

06/02/2026 07:58

Customer Intelligence • run identifier • 6d97d438-74da-48fd-bc2e-b1ec55b18778

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9360F1 Score0.8578Precision • Recall0.8393 0.8770

06/02/2026 07:40

Recommendations • run identifier • f59afa02-d963-4146-8375-bbc4af6249a4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999935R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0042

06/02/2026 07:24

Customer Intelligence • run identifier • f6de8a04-c221-41ce-abdb-ce0837ff98b6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9375F1 Score0.8581Precision • Recall0.8388 0.8784

06/02/2026 07:07

Fraud Detection • run identifier • a3df9cae-b6f9-4f6d-a0d1-aab0e6977538

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9728Precision • Recall0.9989 0.9480

06/02/2026 06:59

Recommendations • run identifier • 311630ac-dd90-41a1-b48d-ef81d9136715

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998489R.M.S.E • M.A.E • M.S.E.0.0138 0.0004 0.0202

06/02/2026 06:43

Customer Intelligence • run identifier • b8f576da-8a5a-445f-b9fa-58af1b2feb98

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9362F1 Score0.8598Precision • Recall0.8370 0.8839

06/02/2026 06:24

Fraud Detection • run identifier • 1e980dcf-dd17-4201-bcb3-7842fda04b87

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9685Precision • Recall0.9941 0.9441

06/02/2026 06:16

Recommendations • run identifier • 4283a392-e319-42f3-ba4f-393c34cb869a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999899R.M.S.E • M.A.E • M.S.E.0.0014 0.0000 0.0052

06/02/2026 06:00

Customer Intelligence • run identifier • e13cfeba-5555-45db-9ac9-5a3ee9e06226

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9359F1 Score0.8596Precision • Recall0.8241 0.8983

06/02/2026 05:45

Recommendations • run identifier • 355453c0-47e1-4516-9915-fb3c7ccac18f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999919R.M.S.E • M.A.E • M.S.E.0.0025 0.0000 0.0047

06/02/2026 05:28

Customer Intelligence • run identifier • e1a04730-25ae-4f50-bf04-cdc619c09af4

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9350F1 Score0.8569Precision • Recall0.8278 0.8882

06/02/2026 05:11

Fraud Detection • run identifier • a055be44-58c2-47a8-981f-323cb7a9ba9d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9954F1 Score0.9666Precision • Recall1.0000 0.9353

06/02/2026 05:04

Recommendations • run identifier • 16320015-33ae-44c0-9b76-d7c8012a552e

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.0.0016 0.0000 0.0050

06/02/2026 04:47

Customer Intelligence • run identifier • 8481c6bb-438b-40ff-b5b0-653cdc59087a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9353F1 Score0.8606Precision • Recall0.8411 0.8810

06/02/2026 04:30

Fraud Detection • run identifier • 6e2c05ef-7f74-4cae-afee-5cc088223640

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9691Precision • Recall0.9931 0.9462

06/02/2026 04:22

Recommendations • run identifier • 48904475-6b0d-437e-89e1-f416d8ad7883

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.0.0031 0.0000 0.0054

06/02/2026 04:05

Customer Intelligence • run identifier • 06ac0fdb-089a-401f-bbc7-b5c945e739b6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9381F1 Score0.8607Precision • Recall0.8380 0.8847

06/02/2026 03:49

Fraud Detection • run identifier • 47ce08b5-e9fc-4eb1-9067-3e5f8a8d9969

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9686Precision • Recall0.9932 0.9452

06/02/2026 03:41

Recommendations • run identifier • e11bdf28-f045-4273-88ad-6f587cd3f74c

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.997635R.M.S.E • M.A.E • M.S.E.0.0178 0.0006 0.0252

06/02/2026 03:24

Customer Intelligence • run identifier • 937f964e-6240-48f8-b9da-57bddb8a7f26

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9349F1 Score0.8597Precision • Recall0.8302 0.8914

06/02/2026 03:07

Fraud Detection • run identifier • 172dbc6b-11e0-4cd6-aa2b-2319b9216b82

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9719Precision • Recall0.9970 0.9480

06/02/2026 02:59

Recommendations • run identifier • 590ebc6d-2407-4945-9cbb-fbe5dd8ac3a4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.996588R.M.S.E • M.A.E • M.S.E.0.0242 0.0009 0.0303

06/02/2026 02:43

Customer Intelligence • run identifier • aa0dd198-001f-42e1-b697-bd20b174fca6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9331F1 Score0.8601Precision • Recall0.8298 0.8927

06/02/2026 02:26

Fraud Detection • run identifier • 6f48c82d-9ad6-475d-928b-20382765a799

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9947F1 Score0.9681Precision • Recall1.0000 0.9382

06/02/2026 02:18

Recommendations • run identifier • 154a1b5a-1b0c-47d7-9a14-aa1fd1687886

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.0.0053 0.0001 0.0078

06/02/2026 02:01

Customer Intelligence • run identifier • 0fc6c29b-8a95-4c11-892e-294d033f61b1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9393F1 Score0.8599Precision • Recall0.8357 0.8856

06/02/2026 01:44

Fraud Detection • run identifier • e748068c-0d4d-4cd5-a69c-e25ab93adafe

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9961F1 Score0.9745Precision • Recall0.9995 0.9508

06/02/2026 01:37

Recommendations • run identifier • b10086f5-0cd8-42f2-8e0b-75473b596f76

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999743R.M.S.E • M.A.E • M.S.E.0.0050 0.0001 0.0084

06/02/2026 01:20

Customer Intelligence • run identifier • 41c78ec1-8cf1-42ae-913a-bb3ee90ffe00

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9367F1 Score0.8625Precision • Recall0.8339 0.8932

06/02/2026 01:03

Fraud Detection • run identifier • 02e8a11d-0836-43f9-847e-398be39c76ea

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9732Precision • Recall0.9965 0.9510

06/02/2026 12:55

Recommendations • run identifier • 2a4d6891-e4fc-4aa1-8651-663ff3d2bc72

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.993396R.M.S.E • M.A.E • M.S.E.0.0318 0.0018 0.0424

06/02/2026 12:38

Customer Intelligence • run identifier • cc3773bd-4049-46ac-859a-8ab19059b1c3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9364F1 Score0.8584Precision • Recall0.8363 0.8816

06/02/2026 12:22

Fraud Detection • run identifier • 987e5fdd-1dc4-43e0-ae51-584ef13b3b8b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9957F1 Score0.9782Precision • Recall1.0000 0.9573

06/02/2026 12:14

Recommendations • run identifier • 42ddf881-743f-4ad8-9a60-9f8682e79d38

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 0.0057

06/01/2026 11:57

Customer Intelligence • run identifier • bc3791e3-4dc6-4d55-b484-2896d006bdf5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9356F1 Score0.8587Precision • Recall0.8280 0.8916

06/01/2026 11:40

Fraud Detection • run identifier • fbb506e6-6d7b-450d-997b-201f88622507

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9957F1 Score0.9705Precision • Recall1.0000 0.9426

06/01/2026 11:33

Recommendations • run identifier • 7ed6dc3f-0763-4991-b8a1-da0d516bad98

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999968R.M.S.E • M.A.E • M.S.E.0.0012 0.0000 0.0029

06/01/2026 11:16

Customer Intelligence • run identifier • 923dac0f-42b8-47e9-827c-ecdee55c5e67

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9372F1 Score0.8617Precision • Recall0.8371 0.8879

06/01/2026 10:59

Fraud Detection • run identifier • 6e8f27ba-24f6-4911-9fd1-5c6df97fcf80

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9745Precision • Recall1.0000 0.9503

06/01/2026 10:51

Recommendations • run identifier • 4734484e-777c-4de4-b287-3952df067bfd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999974R.M.S.E • M.A.E • M.S.E.0.0016 0.0000 0.0026

06/01/2026 10:34

Customer Intelligence • run identifier • 85318bee-eb33-4dc2-afa0-a0a13e2a3f39

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9360F1 Score0.8574Precision • Recall0.8403 0.8753

06/01/2026 10:18

Fraud Detection • run identifier • 92bc5c47-5046-4aac-add1-180a2518ba74

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9961F1 Score0.9782Precision • Recall1.0000 0.9573

06/01/2026 10:10

Recommendations • run identifier • e268680b-0a8f-4ba9-a8c0-23363b4bc008

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999823R.M.S.E • M.A.E • M.S.E.0.0039 0.0000 0.0068

06/01/2026 09:53

Customer Intelligence • run identifier • 8b15c9bf-0460-457f-9ed6-dbfa61ff72fb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9322F1 Score0.8524Precision • Recall0.8296 0.8766

06/01/2026 09:36

Fraud Detection • run identifier • af1b6dd2-a549-4416-add7-51e87d50f761

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9951F1 Score0.9673Precision • Recall1.0000 0.9366

06/01/2026 09:29

Recommendations • run identifier • 7e7f5ce4-5d0a-44a4-b317-da76ba00a36f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999879R.M.S.E • M.A.E • M.S.E.0.0024 0.0000 0.0057

06/01/2026 09:12

Customer Intelligence • run identifier • 7265d7b5-c0ea-46de-b3d2-5f5d96d9a67e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9301F1 Score0.8557Precision • Recall0.8248 0.8889

06/01/2026 08:55

Fraud Detection • run identifier • 4d219528-dec0-4564-9996-e4e16248bea5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9965F1 Score0.9769Precision • Recall1.0000 0.9548

06/01/2026 08:47

Recommendations • run identifier • e7d86e27-ec07-4394-8d89-41c84c8b215f

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 0.0050

06/01/2026 08:30

Customer Intelligence • run identifier • 75be58d2-9906-4d87-93ad-f9a7e925b17b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8584Precision • Recall0.8410 0.8766

06/01/2026 08:14

Fraud Detection • run identifier • 50755609-a809-411c-a0f9-b04ccf4c2a98

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9975F1 Score0.9780Precision • Recall0.9972 0.9596

06/01/2026 08:06

Recommendations • run identifier • 1290c2af-f06a-4176-97c6-2978c6818be5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.993753R.M.S.E • M.A.E • M.S.E.0.0276 0.0016 0.0406

06/01/2026 07:49

Customer Intelligence • run identifier • b9527e2a-56f5-4ab6-a64f-5fe0fcab7f5a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9325F1 Score0.8567Precision • Recall0.8305 0.8846

06/01/2026 07:32

Fraud Detection • run identifier • c80d3d24-a244-4e31-8870-f5ca042aef50

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9961F1 Score0.9721Precision • Recall1.0000 0.9457

06/01/2026 07:25

Recommendations • run identifier • f791dcc1-8784-4228-bb96-1acc35dea0dd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999897R.M.S.E • M.A.E • M.S.E.0.0015 0.0000 0.0052

06/01/2026 07:08

Customer Intelligence • run identifier • 0033f7f6-6a7d-47da-9104-f3344e88a136

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9374F1 Score0.8582Precision • Recall0.8362 0.8814

06/01/2026 06:51

Fraud Detection • run identifier • 0bd1f852-e5c3-4fa9-a033-7bdcceb64d39

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9965F1 Score0.9744Precision • Recall0.9956 0.9542

06/01/2026 06:43

Recommendations • run identifier • 8cafa7cb-41fe-44c8-993b-3d93aa88f8f9

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999630R.M.S.E • M.A.E • M.S.E.0.0062 0.0001 0.0099

06/01/2026 06:26

Customer Intelligence • run identifier • 39a8aba7-4ddf-453e-a8d3-e90fdb094c6a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9383F1 Score0.8604Precision • Recall0.8435 0.8780

06/01/2026 06:10

Fraud Detection • run identifier • bc2d824d-4292-41bd-8cd9-90e1032ac7f7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9951F1 Score0.9660Precision • Recall1.0000 0.9342

06/01/2026 06:02

Recommendations • run identifier • 1a744ff3-4532-4345-85c9-3e7e4592a096

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.996881R.M.S.E • M.A.E • M.S.E.0.0196 0.0008 0.0286

06/01/2026 05:45

Customer Intelligence • run identifier • 92842073-fb0a-4690-a152-f058c30edcea

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9339F1 Score0.8556Precision • Recall0.8281 0.8849

06/01/2026 05:28

Fraud Detection • run identifier • b4ea4031-747c-49e4-b418-27f8b8065749

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9702Precision • Recall1.0000 0.9421

06/01/2026 05:21

Recommendations • run identifier • fd107690-06f3-4a36-88e6-9162adef4fdf

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999973R.M.S.E • M.A.E • M.S.E.0.0010 0.0000 0.0027

06/01/2026 05:04

Customer Intelligence • run identifier • a9f374ce-927b-48dc-94ff-e083df1be53b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9367F1 Score0.8570Precision • Recall0.8345 0.8808

06/01/2026 04:47

Fraud Detection • run identifier • 01704d2b-b756-4755-8059-798618806dc2

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9967F1 Score0.9747Precision • Recall0.9995 0.9512

06/01/2026 04:39

Recommendations • run identifier • fc501d24-18dc-434b-8dc6-4d3a8f69874b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999872R.M.S.E • M.A.E • M.S.E.0.0020 0.0000 0.0058

06/01/2026 04:23

Customer Intelligence • run identifier • bc11bc1c-7f4a-4c31-b768-e81c45fecca3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9382F1 Score0.8613Precision • Recall0.8370 0.8871

06/01/2026 04:06

Fraud Detection • run identifier • 9cb385a7-386f-4a8f-a150-602a5e173aac

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9954F1 Score0.9720Precision • Recall0.9980 0.9472

06/01/2026 03:58

Recommendations • run identifier • 8248105b-00b7-42dc-a41a-c851f9737db8

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999987R.M.S.E • M.A.E • M.S.E.0.0004 0.0000 0.0018

06/01/2026 03:41

Customer Intelligence • run identifier • 68f23a37-4dca-4914-9239-d84f945d33f1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9374F1 Score0.8622Precision • Recall0.8348 0.8913

06/01/2026 03:24

Fraud Detection • run identifier • 77102658-9742-4a0e-9160-555a528a9c82

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9735Precision • Recall1.0000 0.9484

06/01/2026 03:17

Recommendations • run identifier • b673618a-4efd-449b-8a37-bd0f81488b79

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999939R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0040

06/01/2026 03:00

Customer Intelligence • run identifier • ebb14a85-98dc-4f6c-bd97-97bb03b040fa

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9371F1 Score0.8575Precision • Recall0.8366 0.8795

06/01/2026 02:43

Fraud Detection • run identifier • bde19fc8-af37-43df-9bed-cffe4932bd45

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9736Precision • Recall1.0000 0.9487

06/01/2026 02:35

Recommendations • run identifier • 524815b9-abb8-41df-9ecc-0b3bb93fc2e4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999054R.M.S.E • M.A.E • M.S.E.0.0090 0.0003 0.0159

06/01/2026 02:18

Customer Intelligence • run identifier • 08e83feb-a2e3-42fc-a042-66efb3a18af9

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9352F1 Score0.8582Precision • Recall0.8357 0.8819

06/01/2026 02:02

Fraud Detection • run identifier • 7a97b86c-2296-40cd-b370-4dbaf798b479

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9964F1 Score0.9729Precision • Recall1.0000 0.9472

06/01/2026 01:54

Recommendations • run identifier • 166938b3-8632-47ca-8c6f-41c71d807217

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999386R.M.S.E • M.A.E • M.S.E.0.0087 0.0002 0.0128

06/01/2026 01:37

Customer Intelligence • run identifier • 60f83541-04e4-48cd-b212-132e30a08524

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9343F1 Score0.8568Precision • Recall0.8351 0.8797

06/01/2026 01:20

Fraud Detection • run identifier • ca96fa2e-fcfd-4799-ae80-531bbaa6525f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9686Precision • Recall1.0000 0.9390

06/01/2026 01:13

Recommendations • run identifier • dadd3189-8bfe-4b4e-ae0c-c148dd4d2d4f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999893R.M.S.E • M.A.E • M.S.E.0.0027 0.0000 0.0053

06/01/2026 12:56

Customer Intelligence • run identifier • 9ac2f092-9d4f-43c9-a37b-35ded30ea386

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9357F1 Score0.8589Precision • Recall0.8335 0.8859

06/01/2026 12:39

Fraud Detection • run identifier • 48b43e16-6bcf-4974-9b7d-183b11579747

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9959F1 Score0.9727Precision • Recall1.0000 0.9469

06/01/2026 12:31

Recommendations • run identifier • 60755c5a-cb1a-44a2-bac8-b306cb056e03

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.996601R.M.S.E • M.A.E • M.S.E.0.0194 0.0009 0.0301

06/01/2026 12:15

Customer Intelligence • run identifier • 49246b70-4186-41e0-bb65-b913fb72d5b1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9363F1 Score0.8613Precision • Recall0.8322 0.8925

06/01/2026 11:58

Fraud Detection • run identifier • 4664dfe2-599f-4df0-aacd-dd6d2365a401

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9957F1 Score0.9723Precision • Recall1.0000 0.9461

06/01/2026 11:50

Recommendations • run identifier • e0d4755f-7c2f-40bf-942a-f01db9200169

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999938R.M.S.E • M.A.E • M.S.E.0.0015 0.0000 0.0041

06/01/2026 11:33

Customer Intelligence • run identifier • 4ae1c38f-1138-4dfd-91fb-629319952cad

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9367F1 Score0.8596Precision • Recall0.8337 0.8873

06/01/2026 11:16

Fraud Detection • run identifier • b4a931fb-d3be-439a-aefc-2d309d83a3a0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9941F1 Score0.9677Precision • Recall1.0000 0.9375

06/01/2026 11:09

Recommendations • run identifier • de3b89b4-4416-4792-a95a-045eccf494ce

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 0.0051

06/01/2026 10:52

Customer Intelligence • run identifier • 7ace58ab-a0a1-4b6d-9d66-b763ed2463fa

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9345F1 Score0.8571Precision • Recall0.8366 0.8786

06/01/2026 10:35

Fraud Detection • run identifier • 53de2dd8-1eba-49ea-89bb-5e045272d187

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9966F1 Score0.9759Precision • Recall1.0000 0.9529

06/01/2026 10:27

Recommendations • run identifier • 884ca20a-ac13-414d-ab7c-f2f35155946f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998178R.M.S.E • M.A.E • M.S.E.0.0157 0.0005 0.0221

06/01/2026 10:11

Customer Intelligence • run identifier • d212c236-4f8b-4d81-8644-e3c564de344e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9358F1 Score0.8587Precision • Recall0.8348 0.8840

06/01/2026 09:54

Fraud Detection • run identifier • a0a7b50d-95be-47db-993d-eab53f2d1a32

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9960F1 Score0.9720Precision • Recall1.0000 0.9456

06/01/2026 09:46

Recommendations • run identifier • 2a6358a0-3827-413e-bfe4-39434e37753a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999885R.M.S.E • M.A.E • M.S.E.0.0019 0.0000 0.0055

06/01/2026 09:29

Customer Intelligence • run identifier • a3fd539c-d8e6-429b-86ce-6b12ef99284c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9360F1 Score0.8567Precision • Recall0.8360 0.8784

06/01/2026 09:12

Fraud Detection • run identifier • 8e9c8955-0f57-42b5-a976-d08f296df81f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9718Precision • Recall1.0000 0.9452

06/01/2026 09:05

Recommendations • run identifier • d052dc86-cc08-481a-b47a-bc8fd7b280fa

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.0.0026 0.0000 0.0050

06/01/2026 08:48

Customer Intelligence • run identifier • c3f23a53-3b53-4421-9173-4ccf2a02e477

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9363F1 Score0.8605Precision • Recall0.8373 0.8849