ML Training & AutoML
Classification, regression, clustering, dimensionality reduction, and AutoML — 54 algorithms with cross-validation.
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Video walkthrough coming soon
/public/media/ml-training-walkthrough.mp4Supported algorithms (54)
- Classification: Logistic Regression, Random Forest, XGBoost, LightGBM, CatBoost, SVM, KNN, Naïve Bayes, Decision Tree, Extra Trees, AdaBoost, MLP
- Regression: Linear, Ridge, Lasso, ElasticNet, Random Forest, Gradient Boosting, XGBoost, SVR, KNN
- Clustering: K-Means, DBSCAN, Hierarchical, Gaussian Mixture, Spectral, Mean-Shift
- Dimensionality reduction: PCA, t-SNE, UMAP, ICA, factor analysis
- AutoML: trains and tunes a slate of models with Optuna, returns a ranked leaderboard
Evaluation
- Classification: confusion matrix, ROC/PR curves, calibration, SHAP values
- Regression: residual plots, RMSE/MAE/R², feature importance
- Cross-validation: k-fold, stratified, grouped, time-series split