pandrs 0.3.2

A high-performance DataFrame library for Rust, providing pandas-like API with advanced features including SIMD optimization, parallel processing, and distributed computing capabilities
Documentation 
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//! Machine Learning Module
//!
//! This module provides comprehensive machine learning functionality including
//! preprocessing, model training/evaluation, dimensionality reduction, clustering,
//! anomaly detection, automated feature engineering, model selection, and AutoML.

// Core ML modules
pub mod anomaly;
pub mod clustering;
pub mod dimension;
pub mod metrics;
pub mod models;
pub mod pipeline;
pub mod pipeline_extended;
pub mod preprocessing;

// Advanced ML capabilities
pub mod automl;
pub mod feature_engineering;
pub mod model_selection;
pub mod sklearn_compat;

// Model serving and deployment
pub mod serving;

// GPU-accelerated ML functionality (conditionally compiled)
#[cfg(cuda_available)]
pub mod gpu;

// Backward compatibility layer (for legacy code)
pub mod backward_compat;

// Re-export public types and functions
use crate::core::error::{Error, Result};
use crate::dataframe::DataFrame;
use crate::optimized::OptimizedDataFrame;
use std::collections::HashMap;

// Re-export preprocessing tools
pub use preprocessing::{
    Binner, FeatureSelector, ImputeStrategy, Imputer, MinMaxScaler, OneHotEncoder,
    PolynomialFeatures, StandardScaler,
};

// Re-export metrics
pub use metrics::regression::{
    explained_variance_score, mean_absolute_error, mean_squared_error, r2_score,
    root_mean_squared_error,
};

pub use metrics::classification::{accuracy_score, f1_score, precision_score, recall_score};

// Re-export dimensionality reduction
pub use dimension::{TSNEInit, PCA, TSNE};

// Re-export clustering
pub use clustering::{AgglomerativeClustering, DistanceMetric, KMeans, Linkage, DBSCAN};

// Re-export anomaly detection
pub use anomaly::{IsolationForest, LocalOutlierFactor, OneClassSVM};

// Re-export pipeline
pub use pipeline::{Pipeline, PipelineStage, PipelineTransformer};

pub use pipeline_extended::{
    AdvancedPipeline, AdvancedPipelineStage, BinningStrategy, ColumnSchema,
    FeatureEngineeringStage, FeatureOperation, PipelineContext, PipelineExecutionSummary,
    StageExecution, StageMetadata, WindowOperation,
};

// Re-export model functionality
pub use models::{
    train_test_split, CrossValidation, ModelEvaluator, ModelMetrics, SupervisedModel,
    UnsupervisedModel,
};

// For backward compatibility, re-export old module structures
#[allow(deprecated)]
pub use backward_compat::anomaly_detection as anomaly_detection_compat;
#[allow(deprecated)]
pub use backward_compat::models as models_compat;
#[allow(deprecated)]
pub use backward_compat::pipeline as pipeline_legacy;

// Add pipeline compatibility
pub mod pipeline_compat;

// Export compatibility layer (not marked as deprecated since it's an active adapter)
pub use pipeline_compat::{Pipeline as PipelineCompat, Transformer};

// Re-export GPU-accelerated ML functionality when CUDA is enabled
// Note: GPU ML modules are not yet implemented
// #[cfg(feature = "cuda")]
// pub use gpu::{GpuKMeans, GpuModelParams, GpuPCA, GpuTSNE};

// Re-export advanced ML capabilities
pub use automl::{AutoML, AutoMLConfig, AutoMLResult, ModelResult, ModelSearchSpace, TaskType};

pub use feature_engineering::{
    AggregationFunction, AutoFeatureEngineer, FeatureScaler, FeatureSelectionMethod,
    MinMaxScaler as MLMinMaxScaler, ScalingMethod, StandardScaler as MLStandardScaler,
};

pub use model_selection::{
    CrossValidationStrategy, GridSearchCV, ParameterDistribution, RandomizedSearchCV,
    ScoreFunction, Scorer, SearchResultEntry, SearchResults, SelectKBest,
};

pub use sklearn_compat::{
    MinMaxScalerCompat, Pipeline as SklearnPipeline, PipelineStep, SklearnEstimator,
    SklearnPredictor, SklearnTransformer, StandardScalerCompat,
};

// Re-export model serving capabilities
pub use serving::{
    BatchPredictionRequest, BatchPredictionResponse, DeploymentConfig, DeploymentMetrics,
    DeploymentStatus, HealthCheckConfig, HealthStatus, ModelInfo, ModelMetadata, ModelServer,
    ModelServing, ModelServingFactory, MonitoringConfig, PredictionRequest, PredictionResponse,
    ResourceConfig, ScalingConfig, ServerConfig,
};