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@rhiever rhiever released this 23 Jun 13:01
· 1952 commits to master since this release
0.4
3fdf711

In TPOT 0.4, we've made some major changes to the internals of TPOT and added some convenience functions. We've summarized the changes below.

  • Added new sklearn models and preprocessors
    • AdaBoostClassifier
    • BernoulliNB
    • ExtraTreesClassifier
    • GaussianNB
    • MultinomialNB
    • LinearSVC
    • PassiveAggressiveClassifier
    • GradientBoostingClassifier
    • RBFSampler
    • FastICA
    • FeatureAgglomeration
    • Nystroem
  • Added operator that inserts virtual features for the count of features with values of zero
  • Reworked parameterization of TPOT operators
    • Reduced parameter search space with information from a scikit-learn benchmark
    • TPOT no longer generates arbitrary parameter values, but uses a fixed parameter set instead
  • Removed XGBoost as a dependency
    • Too many users were having install issues with XGBoost
    • Replaced with scikit-learn's GradientBoostingClassifier
  • Improved descriptiveness of TPOT command line parameter documentation
  • Removed min/max/avg details during fit() when verbosity > 1
    • Replaced with tqdm progress bar
    • Added tqdm as a dependency
  • Added fit_predict() convenience function
  • Added get_params() function so TPOT can operate in scikit-learn's cross_val_score & related functions
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