What’s new

v0.4.0

Enhancement

  • Support scikit-learn v0.17.x and v0.18.0.
  • Support imbalanced-learn via .imbalance accessor. See Handling imbalanced data.
  • Added pandas_ml.ConfusionMatrix class for easier classification results evaluation. See Confusion matrix.

Bug Fix

  • ModelFrame.columns may not be preserved via .transform using FunctionTransformer, KernelCenterer, MaxAbsScaler and RobustScaler.

v0.3.1

Enhancement

  • inverse_transform now reverts original ModelFrame.columns information.

Bug Fix

  • Assigning Series to ModelFrame.data property raises TypeError

v0.3.0

Enhancement

  • Support xgboost via ModelFrame.xgboost accessor.

v0.2.0

Enhancement

  • ModelFrame.transform can preserve column names for some sklearn.preprocessing transformation.
  • Added ModelSeries.fit, transform, fit_transform and inverse_transform for preprocessing purpose.
  • ModelFrame can be initialized from statsmodels datasets.
  • ModelFrame.cross_validation.iterate and ModelFrame.cross_validation.train_test_split now keep index of original dataset, and added reset_index keyword to control this behaviour.

Bug Fix

  • target kw may be ignored when initializing ModelFrame with np.ndarray and columns kwds.
  • linear_model.enet_path doesn’t accept additional keywords.
  • Initializing ModelFrame with named Series may have duplicated target columns.
  • ModelFrame.target_name may not be preserved when sliced.

v0.1.1

Enhancement

  • Added sklearn.learning_curve, neural_network, random_projection

v0.1.0

  • Initial Release