v0.5.0

Major update:

• Online automl. For example, we support tuning online machine learning library vowpal wabbit.

Minor updates:

• log best model in mlflow
• utility functions to produce normalized confusion matrix and roc or precision-recall curves for each class in multi-class tasks

v0.4.0

Support for general config constraints and metric constraints in hyperparameter tuning

v0.3.5

• micro/macro f1 metrics added for multi-classification
• simple preprocessing of datetime columns
• support lightgbm with customized objective
• bug fix in FLOW^2

v0.3.0

• Search space improvement
• Separation of initial points and low cost partial config in HPO input

v0.2.9

A number of new features and improvements:

• pickle the AutoML object
• get best model per estimator
• bug fix
• add verbose argument in AutoML.fit()
• nni support
• stateless HPO API

v0.2.8

perf improvement for parallel tuning and bug fix

v0.2.6

added support for nested search space
added experimental support for nni
minor bug fix

v0.2.4

make sample_weight right for ensemble; reduced dependency

v0.2.3

minor bug fix for rf

v0.2.2

Enhanced algorithms and implementations of hyperparameter tuning with support for parallel tuning and ray tune;
Support keyword arguments like sample_weight;
Enable mlflow logging.