• Support for Python 3.4 and below has been officially dropped. Also support for scikit-learn 0.20 or below has been dropped.
• The support of a metric function with the signature score_func(y_true, y_pred) for scoring parameter has been dropped.
• Refine StackingEstimator for not stacking NaN/Infinity predication probabilities.
• Fix a bug that population doesn't persist even warm_start=True when max_time_mins is not default value.
• Now the random_state parameter in TPOT is used for pipeline evaluation instead of using a fixed random seed of 42 before. The set_param_recursive function has been moved to export_utils.py and it can be used in exported codes for setting random_state recursively in scikit-learn Pipeline. It is used to set random_state in fitted_pipeline_ attribute and exported pipelines.
• TPOT can independently use generations and max_time_mins to limit the optimization process through using one of the parameters or both.
• .export() function will return string of exported pipeline if output filename is not specified.
• Add SGDClassifier and SGDRegressor into TPOT default configs.
• Documentation has been updated.
• Fix minor bugs.