./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

04/14/2026 05:26

run identifier

• 432d2bfe-4f32-456b-b2f7-4041908f148a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9388F1 Score0.8631Precision • Recall0.8358 0.8923

Recommendations

04/15/2026 12:32

run identifier

• 21c72790-73fc-4366-a96e-ebf6ac974034

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999983R.M.S.E • M.A.E • M.S.E.0.0003 0.0000 0.0022

Fraud Detection

04/14/2026 05:50

run identifier

• 65990020-cf12-4d86-9edb-fc05b69bbcc7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9972F1 Score0.9756Precision • Recall1.0000 0.9524
Live Logs

🧬 Loading data ﹙≈ 3-8 mins; standby﹚

run identifier: befe261...

🌱 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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∈ New Customer Intelligence workflow

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⧉ Training

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∞ Building estimator chain

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⧉ Training

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← ▣ → Splitting data

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✨ Segmenting

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⚡ Data loaded

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🧬 Loading data ﹙≈ 3-8 mins; standby﹚

run identifier: 21aa7de...

🌱 Generating stochastic, realistic synthetic users and activity events

run identifier: 21aa7de...

📝 New client data not found

run identifier: 21aa7de...

⌕ Checking for new training data

run identifier: 21aa7de...

▶ Starting

run identifier: 21aa7de...

✔ Completed

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💾 Persisting model

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🌢 Persisting metrics

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9932

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9931

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9928

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9928

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9934

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9928

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9934

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🍃.ೃ Fast Forest Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9951

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9934

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9928

run identifier: e238712...

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

run identifier: e238712...

λ · 🌳 Fast Tree Binary · AUC (PR) 0.9936

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

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

run identifier: e238712...

Workflow History

04/15/2026 03:52

Customer Intelligence • run identifier • 21aa7dee-484b-4d64-803e-cb0b03af9298

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9376F1 Score0.8611Precision • Recall0.8369 0.8868

04/15/2026 03:36

Fraud Detection • run identifier • e2387129-90ba-445f-962b-6727a8ba8def

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9952F1 Score0.9717Precision • Recall1.0000 0.9450

04/15/2026 03:28

Recommendations • run identifier • f4e601ca-81c7-40fc-89f4-104d79eda111

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999920R.M.S.E • M.A.E • M.S.E.0.0023 0.0000 0.0046

04/15/2026 03:11

Customer Intelligence • run identifier • 7df4b31c-0dee-47c7-8c5f-0a4eb68a3477

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9360F1 Score0.8580Precision • Recall0.8291 0.8891

04/15/2026 02:55

Fraud Detection • run identifier • 8cc3bea9-9431-4b10-b196-df8f4872fb3d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9738Precision • Recall0.9960 0.9526

04/15/2026 02:47

Recommendations • run identifier • d49e8999-2656-4e51-98da-448243800be5

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999522R.M.S.E • M.A.E • M.S.E.0.0080 0.0001 0.0113

04/15/2026 02:30

Customer Intelligence • run identifier • 59c2b79b-8c23-4028-8ffa-8d3831940e84

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9369F1 Score0.8585Precision • Recall0.8332 0.8854

04/15/2026 02:14

Fraud Detection • run identifier • fbce825f-668d-4a70-ae1f-cd42d4f78732

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9946F1 Score0.9686Precision • Recall1.0000 0.9392

04/15/2026 02:06

Recommendations • run identifier • a045a087-acb7-4c8a-86a0-fd908a2ffc0b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999400R.M.S.E • M.A.E • M.S.E.0.0089 0.0002 0.0127

04/15/2026 01:49

Customer Intelligence • run identifier • 582df656-06d2-4ebb-b955-c4f4f2c5bee7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9347F1 Score0.8564Precision • Recall0.8329 0.8814

04/15/2026 01:33

Fraud Detection • run identifier • 536b72c0-9e00-4d0b-83a3-127088b7e577

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9941F1 Score0.9607Precision • Recall0.9831 0.9392

04/15/2026 01:25

Recommendations • run identifier • 729849bb-76a6-49a0-b66a-2702707f0421

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.993624R.M.S.E • M.A.E • M.S.E.0.0308 0.0017 0.0414

04/15/2026 01:08

Customer Intelligence • run identifier • dd7f5dac-4f25-4bee-83d9-07bed82cd7c5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9359F1 Score0.8582Precision • Recall0.8278 0.8908

04/15/2026 12:52

Fraud Detection • run identifier • d9f21b1d-3f65-4a7e-94c3-66e56ac1031f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9950F1 Score0.9723Precision • Recall1.0000 0.9462

04/15/2026 12:44

Recommendations • run identifier • 7f93e84c-7f18-41a7-b3cb-f00494cf9e55

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999981R.M.S.E • M.A.E • M.S.E.0.0005 0.0000 0.0022

04/15/2026 12:27

Customer Intelligence • run identifier • 4e5e6d7b-9617-4267-9718-76debfd15ea3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9361F1 Score0.8605Precision • Recall0.8392 0.8829

04/15/2026 12:11

Fraud Detection • run identifier • ed590712-0176-4496-a3d5-83d9d673a58a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9693Precision • Recall0.9985 0.9418

04/15/2026 12:03

Recommendations • run identifier • 354d98df-5bf0-402f-b9c3-2925e9469bcd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999529R.M.S.E • M.A.E • M.S.E.0.0072 0.0001 0.0112

04/15/2026 11:47

Customer Intelligence • run identifier • de6ab605-8d7c-41db-a531-66aa8a63cd26

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9320F1 Score0.8574Precision • Recall0.8239 0.8938

04/15/2026 11:30

Fraud Detection • run identifier • e1452ef5-bdf4-4ea0-bbf8-73c73da2453b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9956F1 Score0.9728Precision • Recall1.0000 0.9471

04/15/2026 11:22

Recommendations • run identifier • 8314841e-fd8a-46a4-a56a-8fab752fb7aa

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999886R.M.S.E • M.A.E • M.S.E.0.0022 0.0000 0.0056

04/15/2026 11:06

Customer Intelligence • run identifier • 146ca8ce-dd65-44c5-9bc8-e2eb79df54bf

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9377F1 Score0.8597Precision • Recall0.8333 0.8879

04/15/2026 10:49

Fraud Detection • run identifier • 31e8400f-6ada-4135-b4d5-4bc4ef888a51

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9954F1 Score0.9683Precision • Recall1.0000 0.9385

04/15/2026 10:41

Recommendations • run identifier • 5462a44b-82b9-41ab-a9cf-f37351142832

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999967R.M.S.E • M.A.E • M.S.E.0.0016 0.0000 0.0030

04/15/2026 10:25

Customer Intelligence • run identifier • 50f9f987-8d5b-4ddd-bc36-6af52e54a8ee

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9363F1 Score0.8573Precision • Recall0.8310 0.8854

04/15/2026 10:08

Fraud Detection • run identifier • 87e5071a-0034-4ff9-85ba-5af345297618

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9950F1 Score0.9658Precision • Recall1.0000 0.9338

04/15/2026 10:00

Recommendations • run identifier • 27e8b4d1-da0e-4704-9aeb-b01ba48a8661

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999838R.M.S.E • M.A.E • M.S.E.0.0040 0.0000 0.0066

04/15/2026 09:44

Customer Intelligence • run identifier • 80996568-7861-49e9-927a-7d93b434d451

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9362F1 Score0.8581Precision • Recall0.8320 0.8860

04/15/2026 09:27

Fraud Detection • run identifier • 902a5806-3e1a-4255-a2a0-cd585ae34838

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9679Precision • Recall0.9960 0.9413

04/15/2026 09:20

Recommendations • run identifier • 19fd7445-a268-4c9b-bc61-7faf7d77a01b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999302R.M.S.E • M.A.E • M.S.E.0.0098 0.0002 0.0137

04/15/2026 09:03

Customer Intelligence • run identifier • 2866173e-3354-41cd-83e3-bcc61e2d6527

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9361F1 Score0.8567Precision • Recall0.8328 0.8821

04/15/2026 08:46

Fraud Detection • run identifier • 09a0355b-7933-4be8-a797-a37dd09fa4d6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9964F1 Score0.9719Precision • Recall1.0000 0.9453

04/15/2026 08:39

Recommendations • run identifier • 10cf92f8-9f49-4a1a-9e74-9b446ceb7cec

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998629R.M.S.E • M.A.E • M.S.E.0.0135 0.0004 0.0193

04/15/2026 08:22

Customer Intelligence • run identifier • 92f579ce-bc2b-4770-83ae-29b9c5002efc

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9351F1 Score0.8585Precision • Recall0.8310 0.8878

04/15/2026 08:05

Fraud Detection • run identifier • 67efaae1-4f09-4261-98da-2fe084d5751f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9948F1 Score0.9713Precision • Recall1.0000 0.9442

04/15/2026 07:58

Recommendations • run identifier • ce47c8fa-87dd-42ba-903d-db00830aaaf8

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.998276R.M.S.E • M.A.E • M.S.E.0.0155 0.0005 0.0217

04/15/2026 07:41

Customer Intelligence • run identifier • 1dcc97a4-e24b-4014-89cf-e821d477331a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9350F1 Score0.8584Precision • Recall0.8260 0.8934

04/15/2026 07:24

Fraud Detection • run identifier • 44e86c5f-d616-4fbe-9ca4-52841335d99d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9967F1 Score0.9745Precision • Recall1.0000 0.9502

04/15/2026 07:17

Recommendations • run identifier • 9587d212-917f-43cf-8ef2-5beeba10619a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999890R.M.S.E • M.A.E • M.S.E.0.0020 0.0000 0.0055

04/15/2026 07:00

Customer Intelligence • run identifier • be3d75bf-342c-41b8-84ee-adae593c8075

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9336F1 Score0.8588Precision • Recall0.8318 0.8876

04/15/2026 06:43

Fraud Detection • run identifier • b997a355-8b41-4a55-ba1f-544d4f367f6d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9955F1 Score0.9693Precision • Recall1.0000 0.9404

04/15/2026 06:36

Recommendations • run identifier • 44a6b007-3ea7-4f5a-b130-cfe0e328ff77

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999808R.M.S.E • M.A.E • M.S.E.0.0046 0.0001 0.0072

04/15/2026 06:19

Customer Intelligence • run identifier • 9e1a1eb2-2dd8-4c93-aaf2-088251dfeeb4

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9366F1 Score0.8561Precision • Recall0.8311 0.8826

04/15/2026 06:02

Fraud Detection • run identifier • 5a8010d6-5db2-4267-b14c-c8751e9b2e1b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9969F1 Score0.9756Precision • Recall0.9995 0.9527

04/15/2026 05:55

Recommendations • run identifier • dd8da89b-5bbc-4876-9c9f-cbce52303ad6

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999963R.M.S.E • M.A.E • M.S.E.0.0013 0.0000 0.0032

04/15/2026 05:38

Customer Intelligence • run identifier • f6aec41f-8c42-44c5-a12e-546b1063c610

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9335F1 Score0.8542Precision • Recall0.8307 0.8791

04/15/2026 05:22

Fraud Detection • run identifier • 823edb17-fc83-4eee-a193-cefc9a6de3d1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9962F1 Score0.9746Precision • Recall1.0000 0.9504

04/15/2026 05:14

Recommendations • run identifier • 1fea485f-bf52-4a5c-bb32-0d51f5d4b2a7

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.996226R.M.S.E • M.A.E • M.S.E.0.0239 0.0010 0.0322

04/15/2026 04:57

Customer Intelligence • run identifier • c09cf80e-963f-4af2-a8fd-2996a07f9fd0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9362F1 Score0.8621Precision • Recall0.8312 0.8953

04/15/2026 04:41

Fraud Detection • run identifier • 16c32125-bd31-4e5b-8933-6db82dd8a4da

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9672Precision • Recall0.9995 0.9369

04/15/2026 04:33

Recommendations • run identifier • 5d75eb7d-6013-40e2-9025-5c5119438e20

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999900R.M.S.E • M.A.E • M.S.E.0.0027 0.0000 0.0052

04/15/2026 04:16

Customer Intelligence • run identifier • 381be973-d5de-4db5-8071-aa25ab951f37

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9377F1 Score0.8588Precision • Recall0.8367 0.8820

04/15/2026 04:00

Fraud Detection • run identifier • b42fc7a0-485f-44c4-b8a5-f833a405f19e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9955F1 Score0.9728Precision • Recall1.0000 0.9471

04/15/2026 03:52

Recommendations • run identifier • ff820c85-7f90-43f2-82a4-cb321bb84c6d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999894R.M.S.E • M.A.E • M.S.E.0.0017 0.0000 0.0054

04/15/2026 03:36

Customer Intelligence • run identifier • 74ee877a-3388-4397-81a2-7823c9666253

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9377F1 Score0.8589Precision • Recall0.8312 0.8884

04/15/2026 03:17

Fraud Detection • run identifier • 3b147377-aeb6-4805-b05c-b80968bba296

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9957F1 Score0.9705Precision • Recall0.9966 0.9457

04/15/2026 03:09

Recommendations • run identifier • 9802f5f9-075f-43aa-ad9e-271d8fc6df8f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999160R.M.S.E • M.A.E • M.S.E.0.0099 0.0002 0.0152

04/15/2026 02:53

Customer Intelligence • run identifier • 61b49cef-d8cf-453a-ac97-55b5b6746b80

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9357F1 Score0.8559Precision • Recall0.8314 0.8818

04/15/2026 02:35

Recommendations • run identifier • 2a4b28cd-4eec-4bb4-9e2c-2cd3d69931fc

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999802R.M.S.E • M.A.E • M.S.E.0.0049 0.0001 0.0073

04/15/2026 02:18

Customer Intelligence • run identifier • 4628bddb-0c73-4de9-84f7-56dc3a93a89d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9362F1 Score0.8574Precision • Recall0.8374 0.8783

04/15/2026 02:01

Fraud Detection • run identifier • 1b5546b7-f233-4a73-8671-947265004c42

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9955F1 Score0.9675Precision • Recall0.9873 0.9484

04/15/2026 01:54

Recommendations • run identifier • 49e1e1fd-778b-4498-8794-b4629a633a97

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.0.0021 0.0000 0.0059

04/15/2026 01:37

Customer Intelligence • run identifier • 0658b607-1ebb-42cc-b62f-9390535af202

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9364F1 Score0.8598Precision • Recall0.8295 0.8924

04/15/2026 01:20

Fraud Detection • run identifier • d73fa064-f1b6-45a8-8214-ed8d419c23ef

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9947F1 Score0.9714Precision • Recall1.0000 0.9443

04/15/2026 01:13

Recommendations • run identifier • babe4c60-5dc0-4691-8449-9deb38787b75

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999964R.M.S.E • M.A.E • M.S.E.0.0013 0.0000 0.0031

04/15/2026 12:56

Customer Intelligence • run identifier • e044373f-9e60-4658-88a3-f9f3e1bbe0d1

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9338F1 Score0.8561Precision • Recall0.8294 0.8846

04/15/2026 12:40

Fraud Detection • run identifier • af56b4ab-e431-4e05-9533-4261ebb4eb47

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9964F1 Score0.9722Precision • Recall0.9975 0.9481

04/15/2026 12:32

Recommendations • run identifier • 21c72790-73fc-4366-a96e-ebf6ac974034

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999983R.M.S.E • M.A.E • M.S.E.0.0003 0.0000 0.0022

04/15/2026 12:15

Customer Intelligence • run identifier • c9c3177d-2475-499e-b1bf-dbe60b9f386e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9376F1 Score0.8613Precision • Recall0.8353 0.8889

04/14/2026 11:59

Fraud Detection • run identifier • 0658ba59-3b8a-4e2a-bc64-14591cb47e2f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9964F1 Score0.9718Precision • Recall0.9991 0.9461

04/14/2026 11:51

Recommendations • run identifier • fa0ec8ad-8859-43d1-9f72-3f32c3da4509

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.0.0017 0.0000 0.0053

04/14/2026 11:34

Customer Intelligence • run identifier • fe9a500d-a111-4dc4-b4e9-bbb78fd404ec

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9359F1 Score0.8576Precision • Recall0.8336 0.8831

04/14/2026 11:18

Fraud Detection • run identifier • 4b359d2c-ef21-403b-9b8d-6365176b53c9

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9678Precision • Recall0.9988 0.9386

04/14/2026 11:10

Recommendations • run identifier • d6b64620-5748-4861-87d3-b9c627ca6ece

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999840R.M.S.E • M.A.E • M.S.E.0.0039 0.0000 0.0065

04/14/2026 10:54

Customer Intelligence • run identifier • 0b0b5013-cda6-4f2e-8482-65b60a7e74ba

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9362F1 Score0.8591Precision • Recall0.8384 0.8807

04/14/2026 10:37

Fraud Detection • run identifier • be859456-492c-4a94-a516-613caf8eb427

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9969F1 Score0.9748Precision • Recall1.0000 0.9509

04/14/2026 10:29

Recommendations • run identifier • 56f9c24b-7c45-4c2f-8066-60d18faf853f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.985186R.M.S.E • M.A.E • M.S.E.0.0474 0.0039 0.0626

04/14/2026 10:13

Customer Intelligence • run identifier • 5bbe9d54-25ee-4520-83d8-2614d73b423e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9356F1 Score0.8567Precision • Recall0.8342 0.8805

04/14/2026 09:56

Fraud Detection • run identifier • 98802615-9815-42d8-955a-46a302aacee6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9956F1 Score0.9697Precision • Recall0.9906 0.9496

04/14/2026 09:48

Recommendations • run identifier • 5c4a77a1-57b9-4722-90f5-82d6e9b9f4e3

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.996234R.M.S.E • M.A.E • M.S.E.0.0228 0.0010 0.0316

04/14/2026 09:32

Customer Intelligence • run identifier • 67f7a399-da84-4319-a645-95548bb79fed

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9380F1 Score0.8624Precision • Recall0.8294 0.8981

04/14/2026 09:15

Fraud Detection • run identifier • b578da39-3523-40ae-a54f-a2172d165cb0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9703Precision • Recall0.9986 0.9435

04/14/2026 09:07

Recommendations • run identifier • cf982226-a8aa-408a-8bae-732ee7aab448

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.906914R.M.S.E • M.A.E • M.S.E.0.1204 0.0247 0.1570

04/14/2026 08:51

Customer Intelligence • run identifier • a4d91ed5-5170-4500-9693-f1d5c04f960a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9379F1 Score0.8608Precision • Recall0.8418 0.8806

04/14/2026 08:34

Fraud Detection • run identifier • 4b4dcb16-7501-4593-aad3-eb3dafa09e51

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9960F1 Score0.9717Precision • Recall1.0000 0.9449

04/14/2026 08:26

Recommendations • run identifier • 2e945a71-6df1-4fe0-96df-e771bd418dc4

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999915R.M.S.E • M.A.E • M.S.E.0.0014 0.0000 0.0048

04/14/2026 08:10

Customer Intelligence • run identifier • 33ba4fc7-f4d2-4dd7-8f1b-11ab53c1b2fc

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9381F1 Score0.8589Precision • Recall0.8311 0.8887

04/14/2026 07:53

Fraud Detection • run identifier • 03d1c67c-045b-44be-89a9-0e4ba00debed

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9947F1 Score0.9708Precision • Recall1.0000 0.9433

04/14/2026 07:45

Recommendations • run identifier • 7b9f9f8d-baab-4ced-b4b3-9a31ce15817d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.993682R.M.S.E • M.A.E • M.S.E.0.0298 0.0017 0.0410

04/14/2026 07:29

Customer Intelligence • run identifier • 064b713c-63b8-4127-9144-45565aa741b7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9375F1 Score0.8610Precision • Recall0.8374 0.8859

04/14/2026 07:12

Fraud Detection • run identifier • 30cf3cd2-696c-42f6-a0c1-d5eff400facb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9949F1 Score0.9689Precision • Recall0.9976 0.9418

04/14/2026 07:05

Recommendations • run identifier • 5f2e99c7-3bad-4b77-9d90-aaefd77ca45f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999877R.M.S.E • M.A.E • M.S.E.0.0037 0.0000 0.0057

04/14/2026 06:48

Customer Intelligence • run identifier • 573368ac-1ab5-4b2c-b501-7062bc5ca45c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9299F1 Score0.8535Precision • Recall0.8214 0.8883

04/14/2026 06:31

Fraud Detection • run identifier • 07df4f3d-9f95-46b9-a3c3-59bb8d349fd3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9948F1 Score0.9727Precision • Recall1.0000 0.9468

04/14/2026 06:24

Recommendations • run identifier • 47abaa58-8cf7-41cc-833b-7c5ff8b84c95

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999499R.M.S.E • M.A.E • M.S.E.0.0082 0.0001 0.0116

04/14/2026 06:07

Customer Intelligence • run identifier • b61432d0-4361-44f3-9541-4794adb2deee

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9403F1 Score0.8602Precision • Recall0.8404 0.8809

04/14/2026 05:50

Fraud Detection • run identifier • 65990020-cf12-4d86-9edb-fc05b69bbcc7

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9972F1 Score0.9756Precision • Recall1.0000 0.9524

04/14/2026 05:43

Recommendations • run identifier • f553b3c9-6c82-421a-869e-85591e6e937b

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.0.0019 0.0000 0.0053

04/14/2026 05:26

Customer Intelligence • run identifier • 432d2bfe-4f32-456b-b2f7-4041908f148a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9388F1 Score0.8631Precision • Recall0.8358 0.8923

04/14/2026 05:09

Fraud Detection • run identifier • 55648ce9-1400-4ea7-9948-27f8b32e49c0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9944F1 Score0.9685Precision • Recall1.0000 0.9389

04/14/2026 05:02

Recommendations • run identifier • fde9d7fa-73a4-4d3d-960d-b26d013175f3

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999923R.M.S.E • M.A.E • M.S.E.0.0022 0.0000 0.0046

04/14/2026 04:45

Customer Intelligence • run identifier • 00e52430-13a4-4bbf-acee-7a9e20dc155a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9358F1 Score0.8603Precision • Recall0.8359 0.8862

04/14/2026 04:28

Fraud Detection • run identifier • a5bd5ebd-0479-4f52-a931-dc683318798d

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9954F1 Score0.9670Precision • Recall0.9995 0.9364

04/14/2026 04:21

Recommendations • run identifier • 5f999432-1c8d-4e15-a3b2-3bec118c0315

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.0.0023 0.0000 0.0052

04/14/2026 04:04

Customer Intelligence • run identifier • 9ba83245-4066-43b0-90e8-2559a8a0d14b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9352F1 Score0.8598Precision • Recall0.8344 0.8869

04/14/2026 03:47

Fraud Detection • run identifier • 099b1dfa-40e5-43c7-b47b-7f3350a274fb

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9968F1 Score0.9739Precision • Recall1.0000 0.9490

04/14/2026 03:40

Recommendations • run identifier • 8330ba48-e5aa-43d5-a6f6-601b0a07ae02

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999898R.M.S.E • M.A.E • M.S.E.0.0016 0.0000 0.0052

04/14/2026 03:23

Customer Intelligence • run identifier • fcf3c031-d75d-4112-a1fd-6d518dfe1063

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9358F1 Score0.8583Precision • Recall0.8341 0.8840

04/14/2026 03:06

Fraud Detection • run identifier • df979147-ec94-4f9d-b0c4-2c2fa285069a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9950F1 Score0.9653Precision • Recall1.0000 0.9329

04/14/2026 02:59

Recommendations • run identifier • 1e368ab4-e4a4-4179-9f73-507323f27e6f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999784R.M.S.E • M.A.E • M.S.E.0.0040 0.0001 0.0076

04/14/2026 02:42

Customer Intelligence • run identifier • 06fcdf4e-6593-4ea4-9aa7-9dfed46359da

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9353F1 Score0.8560Precision • Recall0.8266 0.8876

04/14/2026 02:26

Fraud Detection • run identifier • 24f8db22-0884-4e70-80b2-b23e514d88f6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9966F1 Score0.9741Precision • Recall1.0000 0.9496

04/14/2026 02:18

Recommendations • run identifier • 797f5380-1fa2-4ec2-b3a9-f84d234bef04

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.0.0028 0.0000 0.0063

04/14/2026 02:01

Customer Intelligence • run identifier • 317c9f04-c35d-43de-8871-7c7159d7dd45

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9360F1 Score0.8585Precision • Recall0.8385 0.8794

04/14/2026 01:45

Fraud Detection • run identifier • 8942828f-4662-471f-bcf1-c9a51361b164

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9965F1 Score0.9721Precision • Recall0.9961 0.9493

04/14/2026 01:37

Recommendations • run identifier • d754f41a-d482-4b19-bb5a-9b285d0b650b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.981252R.M.S.E • M.A.E • M.S.E.0.0524 0.0051 0.0714

04/14/2026 01:20

Customer Intelligence • run identifier • 39493b8e-1deb-4d8c-9e5b-c297edfb2fc0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9345F1 Score0.8584Precision • Recall0.8304 0.8883

04/14/2026 01:04

Fraud Detection • run identifier • 05c9b4f8-be37-453f-89b2-f34d1b17df4c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9962F1 Score0.9706Precision • Recall0.9984 0.9444

04/14/2026 12:56

Recommendations • run identifier • 8377e758-aea5-4207-b39d-fd1971f02231

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999895R.M.S.E • M.A.E • M.S.E.0.0021 0.0000 0.0053

04/14/2026 12:39

Customer Intelligence • run identifier • 26b06c6d-8b7c-454e-a30e-a1d0074056b3

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9333F1 Score0.8569Precision • Recall0.8344 0.8807

04/14/2026 12:23

Fraud Detection • run identifier • e2c5d874-6a35-4971-bce6-6a32d0cfe39a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9958F1 Score0.9702Precision • Recall1.0000 0.9421

04/14/2026 12:15

Recommendations • run identifier • bf0a1b29-6e1e-47fb-bb8d-474cd2a7601b

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999976R.M.S.E • M.A.E • M.S.E.0.0012 0.0000 0.0025

04/14/2026 11:59

Customer Intelligence • run identifier • c443ed60-a1db-43bd-b783-7a54678fa99a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9376F1 Score0.8622Precision • Recall0.8384 0.8873

04/14/2026 11:42

Fraud Detection • run identifier • a319b92a-35a2-4db4-8dba-0091db522669

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9956F1 Score0.9683Precision • Recall0.9977 0.9405

04/14/2026 11:34

Recommendations • run identifier • 3629c28b-85ee-41c0-9b26-f7bad7db6b8a

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999796R.M.S.E • M.A.E • M.S.E.0.0046 0.0001 0.0074

04/14/2026 11:18

Customer Intelligence • run identifier • 3f41cbfb-9e25-4933-a5fd-7fc001cad077

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9369F1 Score0.8611Precision • Recall0.8346 0.8893

04/14/2026 11:01

Fraud Detection • run identifier • 063019e7-7099-4a45-a728-d54b3e36b47e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9964F1 Score0.9735Precision • Recall1.0000 0.9484

04/14/2026 10:53

Recommendations • run identifier • 7a403b80-114d-4580-9b2a-5593804ec6f2

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999981R.M.S.E • M.A.E • M.S.E.0.0006 0.0000 0.0022

04/14/2026 10:37

Customer Intelligence • run identifier • 1cd9c8a0-02a5-4357-8afd-43c450ae8fe6

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9318F1 Score0.8556Precision • Recall0.8317 0.8810

04/14/2026 10:20

Fraud Detection • run identifier • 73e270da-93af-4f86-a6d6-ec0767ade883

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9948F1 Score0.9695Precision • Recall1.0000 0.9408

04/14/2026 10:12

Recommendations • run identifier • 904328af-4113-4c5b-bef5-96b06f6e51d0

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.988409R.M.S.E • M.A.E • M.S.E.0.0412 0.0031 0.0559

04/14/2026 09:56

Customer Intelligence • run identifier • 4a70a4ff-be0f-40d0-a6a4-81400aefdf47

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9336F1 Score0.8551Precision • Recall0.8312 0.8805

04/14/2026 09:39

Fraud Detection • run identifier • 6fe01d90-bf1e-4007-b7a5-98bb729bd35c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9963F1 Score0.9720Precision • Recall1.0000 0.9456

04/14/2026 09:31

Recommendations • run identifier • 73af6809-d9ce-4912-b0ee-f9545801f40d

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999426R.M.S.E • M.A.E • M.S.E.0.0075 0.0002 0.0125

04/14/2026 09:15

Customer Intelligence • run identifier • 63eb63ad-73cd-466f-87cc-148bbc5f48e5

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9337F1 Score0.8536Precision • Recall0.8281 0.8806

04/14/2026 08:58

Fraud Detection • run identifier • 9a3216c0-a073-475f-8b2e-0e6372ff3667

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9966F1 Score0.9755Precision • Recall1.0000 0.9522

04/14/2026 08:51

Recommendations • run identifier • 5c03495f-e19f-4208-9200-0a322b088d9e

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.0.0017 0.0000 0.0050

04/14/2026 08:34

Customer Intelligence • run identifier • 6b9fe783-d855-44b9-8648-4b765cf15f31

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9372F1 Score0.8639Precision • Recall0.8404 0.8887

04/14/2026 08:17

Fraud Detection • run identifier • ffe3041e-1bf1-4c97-bbda-21a4596a1177

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9966F1 Score0.9738Precision • Recall0.9979 0.9509

04/14/2026 08:10

Recommendations • run identifier • efdffda8-e044-4740-a700-2c4803002664

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.998285R.M.S.E • M.A.E • M.S.E.0.0153 0.0005 0.0216

04/14/2026 07:53

Customer Intelligence • run identifier • f62eb70c-868b-48d7-97fc-71422b3abf24

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9370F1 Score0.8618Precision • Recall0.8362 0.8891

04/14/2026 07:36

Fraud Detection • run identifier • a2fa6f54-d0bc-4668-99ba-cf956369ec5b

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9968F1 Score0.9748Precision • Recall1.0000 0.9508

04/14/2026 07:29

Recommendations • run identifier • f80494cb-127b-416f-99bc-f25767d41fcd

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.999081R.M.S.E • M.A.E • M.S.E.0.0109 0.0002 0.0157

04/14/2026 07:12

Customer Intelligence • run identifier • 34138181-302f-47d1-90f2-43b670da556e

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9366F1 Score0.8602Precision • Recall0.8375 0.8842

04/14/2026 06:56

Fraud Detection • run identifier • de541e03-73a0-4c3b-875b-31336bdfae0f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9963F1 Score0.9722Precision • Recall0.9994 0.9464

04/14/2026 06:48

Recommendations • run identifier • ec7ba7ce-18e2-4b52-8247-cc1d3a530637

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999961R.M.S.E • M.A.E • M.S.E.0.0014 0.0000 0.0033

04/14/2026 06:31

Customer Intelligence • run identifier • 284b5cce-7498-4e31-9f55-30c3d2d75b0f

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9371F1 Score0.8600Precision • Recall0.8351 0.8865

04/14/2026 06:15

Fraud Detection • run identifier • 7312856f-09fa-48bd-80af-0dbd30be55c0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9959F1 Score0.9705Precision • Recall1.0000 0.9427

04/14/2026 06:07

Recommendations • run identifier • 2b3a8b56-4c8b-4b9a-9e00-8c2cc26f31b2

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999920R.M.S.E • M.A.E • M.S.E.0.0023 0.0000 0.0047

04/14/2026 05:51

Customer Intelligence • run identifier • da710bf7-2425-4119-8ea4-6ed166ad715a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9355F1 Score0.8592Precision • Recall0.8324 0.8878

04/14/2026 05:34

Fraud Detection • run identifier • f3681c37-af34-4fc9-9cbc-6f8920920965

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryA.U.C.0.9958F1 Score0.9703Precision • Recall0.9977 0.9443

04/14/2026 05:26

Recommendations • run identifier • 2197785f-3fb3-44da-be31-fdc359faba24

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Forest RegressionR²0.995932R.M.S.E • M.A.E • M.S.E.0.0233 0.0011 0.0332

04/14/2026 05:10

Customer Intelligence • run identifier • 33909d84-d0ac-410f-81b9-b56f494c3e3c

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryK-Means++A.U.C.0.9353F1 Score0.8561Precision • Recall0.8296 0.8844

04/14/2026 04:53

Fraud Detection • run identifier • dd38b46f-0276-4641-8a54-6e5c3e97fdfc

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9954F1 Score0.9693Precision • Recall0.9881 0.9511

04/14/2026 04:45

Recommendations • run identifier • 619dacd6-33e6-4bd5-938c-47f759f5510f

Algorithm(s)
R²
R.M.S.E • M.A.E • M.S.E.
Algorithm(s)Fast Tree RegressionR²0.999908R.M.S.E • M.A.E • M.S.E.0.0028 0.0000 0.0050

04/14/2026 04:29

Customer Intelligence • run identifier • d11fb5d4-351e-4480-9fbd-445e9d750a2a

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Forest BinaryK-Means++A.U.C.0.9376F1 Score0.8599Precision • Recall0.8312 0.8907

04/14/2026 04:12

Fraud Detection • run identifier • ceb39db4-2877-490a-8be6-b2656dca38d0

Algorithm(s)
A.U.C.
F1 Score
Precision • Recall
Algorithm(s)Fast Tree BinaryA.U.C.0.9967F1 Score0.9746Precision • Recall0.9972 0.9529

04/14/2026 04:04

Recommendations • run identifier • 3038aac0-fa6b-4592-bf22-dacd87f2f98e

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.0.0023 0.0000 0.0041