ml_preprocessing 5.1.2

Popular algorithms of data preprocessing for machine learning

Changelog

5.1.2

• ml_dataframe 0.2.0 supported

5.1.1

• ml_dataframe dependency updated

5.1.0

• Standardizer entity added
• dtype parameter added as an argument for Pipeline.process method

5.0.4

• Default values for parameters headerPrefix and headerPostfix added where it applicable

5.0.3

• README corrected (ml_dataframe version corrected)

5.0.2

• xrange dependency removed
• ml_dataframe 0.0.11 supported

5.0.1

• xrange package version locked

5.0.0

• Encoder interface changed: there is no more encode method, use process from Pipeable instead
• Normalizer entity added
• normalize operator added

4.0.0

• DataFrame class split up into separate smaller entities
• DataFrame class core moved to separate repository
• Pipeline entity created
• Categorical data encoders implemented Pipeable interface

3.4.0

• DataFrame: encodedColumnRanges added

3.3.0

• ml_linalg 10.0.0 supported

3.2.0

• ml_linalg 9.0.0 supported

3.1.0

• Categorical data processing: encoders parameter added to DataFrame.fromCsv constructor

3.0.0

• xrange library supported: it's possible to provide ZRange object now instead of tuple2 to specify a range of indices

2.0.0

• DataFrame introduced

1.1.0

• Float32x4InterceptPreprocessor added
• readme updated

1.0.0

• Package published