v0.14.0

• Breaking Change
  • Replace Benjamini-Hochberg implementation with statsmodels implementation (#570)
• Refactoring and Documentation
  • travis.yml (#605)
  • gitignore (#608)
  • Fix docstring of c3 (#590)
  • Feature/pep8 (#607)
• Added Features
  • Improve test coverage (#609)
  • Add "autolag" parameter to augmented_dickey_fuller() (#612)
• Bugfixes
  • Feature/pep8 (#607)
  • Fix filtering on warnings with multiprocessing on Windows (#610)
  • Remove outdated logging config (#621)
  • Replace Benjamini-Hochberg implementation with statsmodels implementation (#570)
  • Fix the kernel and the naming of a notebook (#626)

v0.13.0

• Drop python 2.7 support (#568)
• Fixed bugs
  • Fix cache in friedrich_coefficients and agg_linear_trend (#593)
  • Added a check for wrong column names and a test for this check (#586)
  • Make sure to not install the tests folder (#599)
  • Make sure there is at least a single column which we can use for data (#589)
  • Avoid division by zero in energy_ratio_by_chunks (#588)
  • Ensure that get_moment() uses float computations (#584)
  • Preserve index when column_value and column_kind not provided (#576)
  • Add @set_property("input", "pd.Series") when needed (#582)
  • Fix off-by-one error in longest strike features (fixes #577) (#578)
  • Add set_property import (#572)
  • Fix typo (#571)
  • Fix indexing of melted normalized input (#563)
  • Fix travis (#569)
• Remove warnings (#583)
• Update to newest python version (#594)
• Optimizations
  • Early return from change_quantiles if ql >= qh (#591)
  • Optimize mean_second_derivative_central (#587)
  • Improve performance with Numpy's sum function (#567)
  • Optimize mean_change (fixes issue #542) and correct documentation (#574)

v0.12.0

• fixed bugs
  • wrong calculation of friedrich coefficients
  • feature selection selected too many features
  • an ignored max_timeshift parameter in roll_time_series
• add deprecation warning for python 2
• added support for index based features
• new feature calculator
  • linear_trend_timewise
• enable the RelevantFeatureAugmenter to be used in cross validated pipelines
• increased scipy dependency to 1.2.0

v0.11.1

• general performance improvements
• removed hard pinning of dependencies
• fixed bugs
  • the stock price forecasting notebook
  • the multi classification notebook

v0.11.0

• new feature calculators:
  • fft_aggregated
  • cid_ce
• renamed mean_second_derivate_central to mean_second_derivative_central
• add warning if no relevant features were found in feature selection
• add columns_to_ignore parameter to from_columns method
• add distribution module, contains support for distributed feature extraction on Dask