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        "author": "Peter \"fracpete\" Reutemann",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "License :: OSI Approved :: GNU General Public License (GPL)",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "The **python-weka-wrapper** package makes it easy to run\nWeka algorithms and filters from within Python. It offers access to Weka\nAPI using thin wrappers around JNI calls using the **javabridge** package.\n\nForum for project at:\n\nhttps://groups.google.com/forum/#!forum/python-weka-wrapper\n\nChangelog\n=========\n\n0.3.15 (2019-01-11)\n-------------------\n\n- added wrapper classes for association classes that implement `AssociationRuleProducer`\n  (package `weka.associations`): `AssociationRules`, `AssociationRule`, `item`\n- added `to_source` method to `weka.classifiers.Classifier` and `weka.filters.Filter`\n  (underlying Java classes must implement the respective `Sourcable` interface)\n\n\n0.3.14 (2018-10-28)\n-------------------\n\n- fixed logging setup in `weka.core.jvm` to avoid global setting global logging\n  setup to `DEBUG` (thanks to https://github.com/Arnie97)\n\n\n0.3.13 (2018-09-16)\n-------------------\n\n- upgraded to Weka 3.9.3\n- `weka.jar` now included in PyPi package\n- exposed the following methods in `weka.classifiers.Evaluation`:\n  `cumulative_margin_distribution`, `sf_prior_entropy`, `sf_scheme_entropy`\n\n\n0.3.12 (2018-02-18)\n-------------------\n\n- upgraded to Weka 3.9.2\n- properly initializing package support now, rather than adding package jars to classpath\n- added `weka.core.ClassHelper` Java class for obtaining classes and static fields, as\n  javabridge only uses the system class loader\n\n\n0.3.11 (2017-08-23)\n-------------------\n\n- added `check_for_modified_class_attribute` method to `FilterClassifier` class\n- added `complete_classname` method to `weka.core.classes` module, which allows\n  completion of partial classnames like `.J48` to `weka.classifiers.trees.J48`\n  if there is a unique match; `JavaObject.new_instance` and `JavaObject.check_type`\n  now make use of this functionality, allowing for instantiations like\n  `Classifier(cls=\".J48\")`\n- `jvm.start(system_cp=True)` no longer fails with a `KeyError: 'CLASSPATH'` if\n  there is no `CLASSPATH` environment variable defined\n- Libraries `mtl.jar`, `core.jar` and `arpack_combined_all.jar` were added as is\n  to the `weka.jar` in the 3.9.1 release instead of adding their content to it.\n  Repackaged `weka.jar` to fix this issue (https://github.com/fracpete/python-weka-wrapper/issues/52)\n\n\n0.3.10 (2017-01-04)\n-------------------\n\n- `types.double_matrix_to_ndarray` no longer assumes a square matrix\n  (https://github.com/fracpete/python-weka-wrapper/issues/48)\n- `len(Instances)` now returns the number of rows in the dataset (module `weka.core.dataset`)\n- added method `insert_attribute` to the `Instances` class\n- added class method `create_relational` to the `Attribute` class\n- upgraded Weka to 3.9.1\n\n\n0.3.9 (2016-10-19)\n------------------\n\n- `plot_learning_curve` method of module `weka.plot.classifiers` now accepts a list of test sets;\n  `*` is index of test set in label template string\n- added `missing_value()` methods to `weka.core.dataset` module and `Instance` class\n- output variable `y` for convenience method `create_instances_from_lists` in module\n  `weka.core.dataset` is now optional\n- added convenience method `create_instances_from_matrices` to `weka.core.dataset` module to easily create\n  an `Instances` object from numpy matrices (x and y)\n\n\n0.3.8 (2016-05-09)\n------------------\n\n- now works with javabridge 1.0.14 as well\n\n\n0.3.7 (2016-05-04)\n------------------\n\n- upgraded Weka to 3.9.0\n\n\n0.3.6 (2016-04-02)\n------------------\n\n- `Loader.load_file` method now checks whether the dataset file really exists, otherwise a previously loaded\n  file gets loaded again without an error message (seems to be a Weka issue)\n- replaced `org.pentaho.packageManagement` with `weka.core.packageManagement` as the package management code\n  is now part of Weka rather than a third-party library\n- `jvm.start()` no longer tries to load packages and therefore suppresses error message if `$HOME/wekafiles/packages`\n  should not yet exist\n\n\n0.3.5 (2016-01-29)\n------------------\n\n- added support for `weka.core.BatchPredictor` to class `Classifier` in module `weka.classifiers`\n- upgraded Weka to revision 12410 (post 3.7.13) to avoid performance bottleneck when using setOptions method\n- fixed class `SetupGenerator` from module `weka.core.classes`\n- added `load_any_file` method to the `weka.core.converters` module\n- added `save_any_file` method to the `weka.core.converters` module\n- if `GridSearch` instantiation (module `weka.classifiers`) fails, it now outputs message whether package\n  installed and JVM with package support started\n\n\n0.3.4 (2016-01-15)\n------------------\n\n- added convenience method `create_instances_from_lists` to `weka.core.dataset` module to easily create\n  an `Instances` object from numeric lists (x and y)\n- added `get_object_tags` method to `Tags` class from module `weka.core.classes`, to allow obtaining\n  `weka.core.Tag` array from the method of a `JavaObject` rather than a static field (MultiSearch)\n- updated `MultiSearch` wrapper in module `weka.classifiers` to work with the `multi-search` package\n  version 2016.1.15 or later\n\n\n0.3.3 (2015-09-26)\n------------------\n\n- updated to Weka 3.7.13\n- documentation now covers the API as well\n\n\n0.3.2 (2015-06-29)\n------------------\n\n- The `packages` parameter of the `weka.core.jvm.start()` function can be used for specifying an alternative\n  Weka home directory now as well\n- added `train_test_split` method to `weka.core.Instances` class to easily create train/test splits\n- `evaluate_train_test_split` method of `weka.classifiers.Evaluation` class now uses the `train_test_split` method\n\n\n0.3.1 (2015-04-23)\n------------------\n\n- added `get_tags` class method to `Tags` method for easier instantiation of Tag arrays\n- added `find` method to `Tags` class to locate `Tag` object that matches the string\n- fixed `__getitem__` and `__setitem__` methods of the `Tags` class\n- added `GridSearch` meta-classifier with convenience properties to module `weka.classifiers`\n- added `SetupGenerator` and various parameter classes to `weka.core.classes`\n- added `MultiSearch` meta-classifier with convenience properties to module `weka.classifiers`\n- added `quote`/`unquote` and `backquote`/`unbackquote` methods to `weka.core.classes` module\n- added `main` method to `weka.core.classes` for operations on options: join, split, code\n- added support for option handling to `weka.core.classes` module\n\n\n0.3.0 (2015-04-15)\n------------------\n\n- added method `ndarray_to_instances` to `weka.converters` module for converting Numpy 2-dimensional array into `Instances` object\n- added method `plot_learning_curve` to `weka.plot.classifiers` module for creating learning curves for multiple classifiers for a specific metric\n- added plotting of experiments with `plot_experiment` methid in `weka.plot.experiments` module\n- `Instance.create_instance` method now takes list of tuples (index, internal float value) when generating sparse instances\n- added `weka.core.database` module for loading data from a database\n- added `make_copy` class method to `Clusterer` class\n- added `make_copy` class method to `Associator` class\n- added `make_copy` class method to `Filter` class\n- added `make_copy` class method to `DataGenerator` class\n- most classes (like Classifier and Filter) now have a default classname value in the constructor\n- added `TextDirectoryLoader` class to `weka.core.converters`\n- moved all methods from `weka.core.utils` to `weka.core.classes`\n- fixed `Attribute.index_of` method for determining label index\n- fixed `Attribute.add_string_value` method (used incorrect JNI parameter)\n- `create_instance` and `create_sparse_instance` methods of class `Instance` now ensure that list values are float\n- added `to_help` method to `OptionHandler` class which outputs a help string generated from the base class's\n  `globalInfo` and `listOptions` methods\n- fixed `test_model` method of `Evaluation` class when supplying a `PredictionOutput` object (previously generated `No dataset structure provided!` exception)\n- added `batch_finished` method to `Filter` class for incremental filtering\n- added `line_plot` method to `weka.plot.dataset` module for plotting dataset using internal format (one line plot per instance)\n- added `is_serializable` property to `JavaObject` class\n- added `has_class` convenience property to `Instance` class\n- added `__repr__` method to `JavaObject` classes (simply calls `toString()` method)\n- added `Stemmer` class in module `weka.core.stemmers`\n- added `Stopwords` class in module `weka.core.stopwords`\n- added `Tokenizer` class in module `weka.core.tokenizers`\n- added `StringToWordVector` filter class in module `weka.filters`\n- added simple workflow engine (see documentation on *Flow*)\n\n\n0.2.2 (2015-01-05)\n------------------\n\n- added convenience methods `no_class` (to unset class) and `has_class` (class set?) to `Instances` class\n- switched to using faster method objects for methods `classify_instance`/`distribution_for_instance` in `Classifier` class\n- switched to using faster method objects for methods `cluster_instance`/`distribution_for_instance` in `Clusterer` class\n- switched to using faster method objects for methods `class_index`, `is_missing`, `get/set_value`, `get/set_string_value`, `weight` in `Instance` class\n- switched to using faster method objects for methods `input`, `output`, `outputformat` in `Filter` class\n- switched to using faster method objects for methods `attribute`, `attribute_by_name`, `num_attributes`, `num_instances`,\n  `class_index`, `class_attribute`, `set_instance`, `get_instance`, `add_instance` in `Instances` class\n\n\n0.2.1 (2015-01-05)\n------------------\n\n- added unit testing framework\n- added method `refresh_cache()` to `weka/core/packages.py` to allow user to refresh local cache\n- method `get_classname` in `weka.core.utils` now handles Python objects and class objects as well\n- added convenience method `get_jclass` to `weka.core.utils` to instantiate a Java class\n- added a `JavaArray` wrapper for  `arrays`, which allows getting/setting elements and iterating\n- added property `classname` to class `JavaObject` for easy access to classname of underlying object\n- added class method `parse_matlab` for parsing Matlab matrix strings to `CostMatrix` class\n- `predictions` method of `Evaluation` class now return `None` if predictions are discarded\n- `Associator.get_capabilities()` method is now a property: `Associator.capabilities`\n- added wrapper classes for Java enums: `weka.core.classes.Enum`\n- fixed retrieval of `sumSq` in `Stats` class (used by `AttributeStats`)\n- fixed `cluster_instance` method in `Clusterer` class\n- fixed `filter` and `clusterer` properties in clusterer classes (`SingleClustererEnhancer`, `FilteredClusterer`)\n- added `crossvalidate_model` method to `ClusterEvaluation`\n- added `get_prc` method to 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