sklearn-weka-plugin 0.0.8

Library for making Weka algorithms available within scikit-learn. Relies on the python-weka-wrapper3 library.

The sklearn-weka-plugin library integrates Weka algorithms in scikit-learn using Python 3. It makes use of the python-weka-wrapper3 library for handling the Java Virtual Machine.

Examples can be found at:

https://github.com/fracpete/sklearn-weka-plugin-examples

Changelog

0.0.8 (2024-04-08)

• using scikit-learn instead of deprecated sklearn dependency for scikit-learn (https://github.com/fracpete/sklearn-weka-plugin/pull/10)

0.0.7 (2023-07-07)

• WekaEstimator (module sklweka.classifiers) now has a custom score method that distinguishes between classification and regression to return the correct score.

• renamed data to X and targets to y, since some sklearn schemes use named arguments

• added dummy argument sample_weight=None to fit, score and fit_predict methods

• fixed: when supplying Classifier or JBObject instead of classname/options, classname/options now get determined automatically

• method to_instance (module: sklweka.dataset) now performs correct missing value check

• method to_nominal_labels (module: sklweka.dataset) generates nicer labels now

0.0.6 (2022-04-26)

• WekaEstimator (module sklweka.classifiers) and WekaCluster (module sklweka.clusters) now allow specifying how many labels a particular nominal attribute or class attribute has (to avoid error message like Cannot handle unary class attribute! if there is only one label present in a particular split)

0.0.5 (2022-04-01)

• the to_nominal_attributes method in the sklearn.dataset module requires now the indices parameter (incorrectly declared as optional); can parse a range string now as well

• fixed the fit, set_params and __str__ methods fo the MakeNominal transformer (module sklweka.preprocessing)

• WekaEstimator (module sklweka.classifiers) and WekaCluster (module sklweka.clusters) now allow specifying which attributes to turn into nominal ones, which avoids having to manually convert the data (either as list with 0-based indices or range string with 1-based indices)

• set_params methods now ignore empty dictionaries

0.0.4 (2021-12-17)

• fixed sorting of labels in to_instances method in module sklweka.dataset

• redoing X when no class present in load_arff method (module sklweka.dataset)

• added load_dataset method in module sklweka.dataset that uses Weka to load the data before converting it into sklearn data structures (slower, but more flexible)

0.0.3 (2021-10-26)

• added support for generating data via Weka’s data generators

0.0.2 (2021-04-12)

• requiring python-weka-wrapper3 version 0.2.1 at least in order to offer pickle support

0.0.1 (2021-03-28)

• initial release