Expand description
Machine learning pipeline integration
This module provides integration utilities for common ML frameworks and pipelines:
- Model training data preparation
- Cross-validation utilities
- Feature engineering pipelines
- Model evaluation and metrics
- Integration with popular ML libraries
Modules§
- convenience
- Convenience functions for ML pipeline integration
Structs§
- Cross
Validation Results - Cross-validation results
- Data
Split - Data split for ML training
- Dataset
Info - Dataset information for experiments
- Experiment
Results - Experiment results
- Fold
Result - Result for a single fold
- MLExperiment
- ML experiment tracking
- MLPipeline
- ML pipeline for data preprocessing and preparation
- MLPipeline
Config - Configuration for ML pipeline integration
- Model
Config - Model configuration
- Scaler
Params - Parameters for fitted scalers
Enums§
- Scaling
Method - Feature scaling methods