Release Notes

0.13.0

Breaking Changes

• crossover_probability default changed from 0.2 → 0.8; mutation_probability default changed from 0.8 → 0.1 for both GASearchCV and GAFeatureSelectionCV.

• diversity_control now defaults to True and diversity_threshold now defaults to 0.25. Previously diversity_control defaulted to False and diversity_threshold defaulted to 0.1. Set diversity_control=False to restore the previous behavior.

• The fitness function for GASearchCV is now single-objective (CV score only). Previously a novelty_score based on Hamming distance was included as a second objective. This caused Pareto-dominance comparisons to favor diverse-but-lower-scoring candidates over better candidates, reducing search quality. Fitness sharing and diversity control already maintain population diversity without corrupting the primary fitness signal. GAFeatureSelectionCV retains its two-objective fitness (CV score + feature count) unchanged.

New Features

• Parallel candidate evaluation: candidates within a generation are de-duplicated and unique candidates are evaluated in parallel via n_jobs. Added parallel_backend ("auto", "population", "cv") to control the parallelism strategy.

• fit_stats_: new attribute with evaluation counters — evaluated_candidates, unique_candidates, cross_validate_calls, cache_hits, duplicate_candidates, skipped_invalid_candidates, random_immigrants, local_refinement_candidates.

• Optimizer telemetry in history: new per-generation fields — genotype_diversity, unique_individual_ratio, fitness_best, stagnation_generations, diversity_control_triggered, and others.

• Smart initialization: PopulationConfig(initializer="smart") uses Latin hypercube sampling for numeric parameters, estimator defaults, warm-start seeds, and stratified categorical values. Set initializer="random" to use the previous behavior.

• Grouped config objects: EvolutionConfig, PopulationConfig, RuntimeConfig, and OptimizationConfig provide a cleaner API for advanced settings. The previous flat keyword parameters remain supported for backward compatibility.

• Local search: OptimizationConfig(local_search=True) runs a short neighborhood search around hall-of-fame candidates after the genetic search.

• Fitness sharing: OptimizationConfig(fitness_sharing=True) reduces the fitness of individuals in crowded niches to promote niche exploration.

• Adaptive tournament selection: adaptive_selection=True adjusts selection pressure based on population diversity and stagnation.

• Final selection: final_selection=True re-evaluates the top-K candidates after the GA and selects the best before refitting.

• Uniform crossover: GASearchCV now uses cxUniform (50% per-gene swap probability) instead of two-point crossover for mixed-type hyperparameter spaces.

• Compact verbose log: the generation log now shows div, unique, stag, and events columns.

• Expanded plots: plot_fitness_evolution supports multiple metrics and smoothing; plot_history can visualize arbitrary telemetry fields; plot_search_space adds pair-plot mode and correlation heatmap.

Bug Fixes

• Fixed fitted estimator persistence by excluding volatile DEAP runtime objects from the saved state.
• Fixed type preservation for hyperparameter candidates across all population operations.
• Fixed smart feature-selection initialization to respect max_features and always select at least one feature.
• Fixed convergence telemetry so local refinement updates the final generation history row.

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0.12.0

• Added compatibility for outlier detection algorithms.

0.11.1

• Fixed AttributeError: 'GASearchCV' object has no attribute 'creator'.

0.11.0

• Added use_cache parameter (default True) to skip re-evaluating already-seen configurations.
• Added warm_start_configs to GAFeatureSelectionCV.
• Introduced novelty search strategy to GASearchCV (later revised in 0.13.0).

0.10.0

• GAFeatureSelectionCV now mimics the scikit-learn FeatureSelection API.
• Improved candidate generation when max_features is set.
• Dropped Python 3.7 support; added Python 3.10+ support.

0.9.0

• Introduced adaptive schedulers: ConstantAdapter, ExponentialAdapter, InverseAdapter, PotentialAdapter.
• Added random_state parameter to Continuous, Categorical, and Integer.

0.8.0

• Added max_features to GAFeatureSelectionCV.
• Added multi-metric evaluation support.
• Training now gracefully handles KeyboardInterrupt, SystemExit, StopIteration.

0.7.0

• Added GAFeatureSelectionCV for wrapper-based feature selection.

0.6.0

• Added ProgressBar, TensorBoard, TimerStopping callbacks.
• Added on_start / on_end lifecycle hooks to BaseCallback.
• Seaborn and MLflow are now optional extras.

0.5.0

• Built-in MLflow integration via MLflowConfig.
• Added LogbookSaver callback.

0.4.0

• Added ConsecutiveStopping, ThresholdStopping, DeltaThreshold callbacks.
• Added plot_search_space function.
• Sphinx documentation on Read the Docs.

0.1–0.3

• Initial release of GASearchCV.
• Added param_grid, plot_fitness_evolution, DEAP integration.
• Added Space, Integer, Continuous, Categorical classes.