v0.2.3 - 2019-11-14

New Primitives

Add primitive to make window_sequences based on cutoff times - Issue #217 by @csala
Create a keras LSTM based TimeSeriesClassifier primitive - Issue #218 by @csala
Add pandas DataFrame primitives - Issue #214 by @csala
Add featuretools.EntitySet.normalize_entity primitive - Issue #209 by @csala

Primitive Improvements

Make featuretools.EntitySet.entity_from_dataframe entityset arg optional - Issue #208 by @csala

Add text regression dataset - Issue #206 by @csala

Bug Fixes

pandas.DataFrame.resample crash when grouping by integer columns - Issue #211 by @csala

v0.2.2 - 2019-10-08

New Primitives

• Add primitives for GAN based time-series anomaly detection - Issue #200 by @AlexanderGeiger
• Add numpy.reshape and numpy.ravel primitives - Issue #197 by @AlexanderGeiger
• Add feature selection primitive based on Lasso - Issue #194 by @csala

Primitive Improvements

• feature_extraction.CategoricalEncoder support dtype category - Issue #196 by @csala

v0.2.1 - 2019-09-09

New Primitives

• Timeseries Intervals to Mask Primitive - Issue #186 by @AlexanderGeiger
• Add new primitive: Arima model - Issue #168 by @AlexanderGeiger

Primitive Improvements

• Curate PCA primitive hyperparameters - Issue #190 by @AlexanderGeiger
• Add option to drop rolling window sequences - Issue #186 by @AlexanderGeiger

Bug Fixes

• scikit-image==0.14.3 crashes when installed on Mac - Issue #188 by @csala

v0.2.0 - 2019-07-11

New Features

• Publish the pipelines as an entry_point Issue #175 by @csala

Primitive Improvements

• Improve pandas.DataFrame.resample primitive Issue #177 by @csala
• Improve feature_extractor primitives Issue #183 by @csala
• Improve find_anomalies primitive Issue #180 by @AlexanderGeiger

Bug Fixes

• Typo in the primitive keras.Sequential.LSTMTimeSeriesRegressor Issue #176 by @DanielCalvoCerezo

v0.1.10

New Features

• Add function to run primitives without a pipeline Issue #43 by @csala

New Pipelines

• Add pipelines for all the MLBlocks examples Issue #162 by @csala

Primitive Improvements

• Add Early Stopping to keras.Sequential.LSTMTimeSeriesRegressor primitive Issue #156 by @csala
• Make FeatureExtractor primitives accept Numpy arrays Issue #165 by @csala
• Add window size and pruning to the timeseries_anomalies.find_anomalies primitive Issue #160 by @csala

v0.1.9

New Features

• Add a single table binary classification dataset Issue #141 by @csala

New Primitives

• Add Multilayer Perceptron (MLP) primitive for binary classification Issue #140 by @Hector-hedb12
• Add primitive for Sequence classification with LSTM Issue #150 by @Hector-hedb12
• Add VGG-like convnet primitive Issue #149 by @Hector-hedb12
• Add Multilayer Perceptron (MLP) primitive for multi-class softmax classification Issue #139 by @Hector-hedb12
• Add primitive to count feature matrix columns Issue #146 by @csala

Primitive Improvements

• Add additional fit and predict arguments to keras.Sequential Issue #161 by @csala
• Add suport for keras.Sequential Callbacks Issue #159 by @csala
• Add fixed hyperparam to control keras.Sequential verbosity Issue #143 by @csala

v0.1.8

New Primitives

• mlprimitives.custom.timeseries_preprocessing.time_segments_average - Issue #137

New Features

• Add target_index output in timseries_preprocessing.rolling_window_sequences - Issue #136

v0.1.7

General Improvements

• Validate JSON format in make lint - Issue #133
• Add demo datasets - Issue #131
• Improve featuretools.dfs primitive - Issue #127

New Primitives

• pandas.DataFrame.resample - Issue #123
• pandas.DataFrame.unstack - Issue #124
• featuretools.EntitySet.add_relationship - Issue #126
• featuretools.EntitySet.entity_from_dataframe - Issue #126

Bug Fixes

• Bug in timeseries_anomalies.py - Issue #119

v0.1.6

General Improvements

• Add Contributing Documentation
• Remove upper bound in pandas version given new release of featuretools v0.6.1
• Improve LSTMTimeSeriesRegressor hyperparameters

New Primitives

• mlprimitives.candidates.dsp.SpectralMask
• mlprimitives.custom.timeseries_anomalies.find_anomalies
• mlprimitives.custom.timeseries_anomalies.regression_errors
• mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences
• mlprimitives.custom.timeseries_preprocessing.time_segments_average
• sklearn.linear_model.ElasticNet
• sklearn.linear_model.Lars
• sklearn.linear_model.Lasso
• sklearn.linear_model.MultiTaskLasso
• sklearn.linear_model.Ridge

v0.1.5

New Primitives

• sklearn.impute.SimpleImputer
• sklearn.preprocessing.MinMaxScaler
• sklearn.preprocessing.MaxAbsScaler
• sklearn.preprocessing.RobustScaler
• sklearn.linear_model.LinearRegression

General Improvements

• Separate curated from candidate primitives
• Setup entry_points in setup.py to improve compaitibility with MLBlocks
• Add a test-pipelines command to test all the existing pipelines
• Clean sklearn example pipelines
• Change the author entry to a contributors list
• Change the name of mlblocks_primitives folder
• Fix installation instructions

Bug Fixes

• Fix LSTMTimeSeriesRegressor primitive. Issue #90
• Fix timeseries primitives. Issue #91
• Negative index anomalies in timeseries_errors. Issue #89
• Keep pandas version below 0.24.0. Issue #87