pythonoptunaafter-worktutorial
Optuna hyperparameter tuning after work: study, trial, and early stop
After-work guide to optuna hyperparameter tuning: define a search space and let trials compete honestly. Educational only. Not investment advice.
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Tag: optuna
After-work guide to optuna hyperparameter tuning: define a search space and let trials compete honestly. Educational only. Not investment advice.
Optuna 5.0.0: single-obj default → Multivariate TPE (+ constant liar, enhanced bandwidth); multi-obj NSGA-II → Multi-Objective TPE; importance → PED-ANOVA. Same seed may diverge after ~trial 10. Revert: TPESampler(multivariate=False, constant_liar=False). Not investment advice.