RustKernel Statistical ML

GPU-accelerated machine learning kernels for clustering, anomaly detection, and regression.

Kernels

Clustering (3 kernels)

• KMeans - Lloyd's algorithm with K-Means++ initialization
• DBSCAN - Density-based clustering with GPU union-find
• HierarchicalClustering - Agglomerative clustering

Anomaly Detection (2 kernels)

• IsolationForest - Ensemble of isolation trees
• LocalOutlierFactor - k-NN density estimation

Streaming Anomaly Detection (2 kernels)

• StreamingIsolationForest - Online anomaly detection with sliding window
• AdaptiveThreshold - Self-adjusting thresholds with drift detection

Ensemble (1 kernel)

• EnsembleVoting - Weighted majority voting

Regression (2 kernels)

• LinearRegression - OLS via normal equations
• RidgeRegression - L2 regularization

Explainability (2 kernels)

• SHAPValues - Kernel SHAP for feature explanations
• FeatureImportance - Permutation-based feature importance

NLP / LLM Integration (2 kernels)

• EmbeddingGeneration - Text embedding via hash-based features
• SemanticSimilarity - Multi-metric semantic similarity

Federated Learning (1 kernel)

• SecureAggregation - Privacy-preserving model aggregation

Healthcare Analytics (2 kernels)

• DrugInteractionPrediction - Multi-drug interaction prediction
• ClinicalPathwayConformance - Treatment guideline checking