Expand description
Multi-Task Ensemble Methods
This module provides ensemble methods for multi-task learning, where multiple related learning tasks are solved jointly to improve generalization performance by leveraging information shared across tasks.
Structs§
- Convergence
Info - Convergence information for multi-task training
- Multi
Task Ensemble Classifier - Multi-task ensemble classifier
- Multi
Task Ensemble Config - Configuration for multi-task ensemble learning
- Multi
Task Ensemble Config Builder - Multi
Task Ensemble Regressor - Multi-task ensemble regressor
- Multi
Task Ensemble Regressor Builder - Multi
Task Feature Selector - Multi-task feature selector
- Multi
Task Training Results - Results from multi-task training
- Task
Data - Task-specific training data
- Task
Hierarchy - Task hierarchy for hierarchical sharing
- Task
Metrics - Metrics for individual tasks
Enums§
- Cross
Task Validation - Cross-task validation strategies
- Task
Sharing Strategy - Strategies for sharing information between tasks
- Task
Similarity Metric - Metrics for measuring task similarity
- Task
Weighting Strategy - Strategies for weighting different tasks
Traits§
- Multi
Task Estimator - A trait that combines the
EstimatorandPredicttraits.