This is the release note of v1.5.0.

Highlights

LightGBM Tuner with Cross-validation

LightGBM tuner, which provides efficient stepwise parameter tuning for LightGBM, supports cross-validation as an experimental feature with LightGBMTunerCV. See #1156 for details.

NSGA-II

A sampler based on NSGA-II, a well-known multi-objective optimization algorithm, is now available as the default multi-objective sampler.
The following benchmark result, on the ZDT1 function, shows that NSGA-II outperforms random sampling.
Please refer to #1163 for further details.

Mean Decrease Impurity (MDI) Hyperparameter Importance Evaluator

The default hyperparameter importance evaluator is replaced with a naive mean decrease impurity algorithm. It uses the random forest feature importances in Scikit-learn and therefore requires this package. See #1253 for more details.

optuna.TrialPruned Alias

optuna.TrialPruned is a new alias for optuna.exceptions.TrialPruned. It is now possible to write shorter and more readable code when pruning trials. See #1204 for details.

New Features

• Add a method to stop study.optimize. (#1025)
• Use --study-name instead of --study in CLI commands. (#1079, thanks @seungjaeryanlee!)
• Add cross-validation support for LightGBMTuner. (#1156)
• Add NSGA-II based multi-objective sampler. (#1163)
• Implement log argument for suggest_int. (#1201, thanks @nzw0301!)
• Import optuna.exceptions.TrialPruned in __init__.py. (#1204)
• Mean Decrease Impurity (MDI) hyperparameter importance evaluator. (#1253)

Enhancements

• Add storage cache. (#1140)
• Fix _get_observation_pairs for conditional parameters. (#1166, thanks @y0z!)
• Alternative implementation to hide the interface so that all samplers can use HyperbandPruner. (#1196)
• Fix for O(N) queries being produced if even a single trial is cached. (#1259, thanks @zzorba!)
• Move caching mechanism from RDBStorage to _CachedStorage. (#1263)
• Cache study-related info in _CachedStorage. (#1264)
• Move deep-copies for optimization speed improvement. (#1274)
• Implement log argument for suggest_int of ChainerMN integration. (#1275, thanks @nzw0301!)
• Add warning when Trial.suggest_int modifies high. (#1276)
• Input validation for IntLogUniformDistribution. (#1279, thanks @himkt!)

Bug Fixes

• Support multiple studies in InMemoryStorage. (#1228)
• Fix out of bounds error of CMA-ES. (#1231)
• Fix sklearn - skopt version incompatibility. (#1236)
• Fix a type casting error when using CmaEsSampler. (#1240)
• Upgrade the version of cmaes. (#1242)

Documentation

• Rename test_ to valid_ in docs and docstring. (#1167, thanks @himkt!)
• Add storage specification to BaseStorage class doc. (#1174)
• Add docstring to BaseStorage method interfaces. (#1175)
• Add an explanation of failed trials from samplers' perspective. (#1214)
• Add LightGBMTuner reference. (#1217)
• Modifying code examples to include training data. (#1221)
• Ask optuna tag in Stack Overflow question. (#1249)
• Add notes for auto argument values in HyperbandPruner and SuccessiveHalvingPruner. (#1252)
• Add description of observation_key in XGBoostPruningCallback. (#1260)
• Cosmetic fixes to documentation in BaseStorage. (#1261)
• Modify documentation and fix file extension in the test for AllenNLP integration. (#1265, thanks @himkt!)
• Fix experimental decorator to decorate a class properly. (#1285, thanks @harupy!)

Examples

• Add pruning to PyTorch example. (#1119)
• Use dump_best_config in example. (#1225, thanks @himkt!)
• Stop suggesting using deprecated option in AllenNLP example. (#1282)
• Add link to regression example in the header of keras_integration.py. (#1301, thanks @zishiwu123!)

Tests

• Increase test coverage of storage tests for single worker cases. (#1191)
• Fix sklearn - skopt version incompatibility. (#1236)

Code Fixes

• Dissect trial.py. (#1210, thanks @himkt!)
• Rename trial/*.py to trial/_*.py. (#1239)
• Add type hints to contour.py. (#1254, thanks @bigbird555!)
• Consistent Hyperband bracket ID variable names. (#1262)
• Apply minor code fix to #1201. (#1273)
• Avoid mutable default argument in AllenNLPExecutor.__init__. (#1280)
• Reorder arguments of Trial.suggest_float. (#1292)
• Fix unintended change on calculating n_brackets in HyperbandPruner. (#1294)
• Add experimental decorator to LightGBMTuner and LightGBMTunerCV. (#1305)

Continuous Integration

• Add GitHub action that posts link to documentation. (#1247, thanks @harupy!)
• Add a workflow to create distribution packages. (#1283)
• Stop setting environment variables for GitHub Package. (#1296)