0.4.4 - 2019-11-11

• PyPI
• GitHub

This release was mainly made to provide access to wheels <https://pythonwheels.com/>_ for Windows and MacOS.

ensemble

• Added ensemble.AdaBoostClassifier.

linear_model

• Added a clip_gradient parameter to linear_model.LinearRegression and linear_model.LogisticRegression. Gradient clipping was already implemented, but the maximum absolute value can now be set by the user.
• The intercept_lr parameter of linear_model.LinearRegression and linear_model.LogisticRegression can now be passed an instance of optim.schedulers.Scheduler as well as a float.

metrics

• Fixed metrics.SMAPE, the implementation was missing a multiplication by 2.

optim

• Added optim.schedulers.Optimal produces results that are identical to sklearn.linear_model.SGDRegressor and sklearn.linear_model.SGDClassifier when setting their learning_rate parameter to 'optimal'.

time_series

• Added time_series.SNARIMAX, a generic model which encompasses well-known time series models such as ARIMA and NARX.