Python-weka-wrapper3

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- added `weka.core.systeminfo` module for obtaining output from `weka.core.SystemInfo`
- added `system_info` parameter to `weka.core.jvm.start()` method
- merged PR 33 (https://github.com/fracpete/python-weka-wrapper3/pull/33) to better handle
associator output

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- added `AttributeSelectedClassifier` meta-classifier to module `weka.classifiers`
- added `AttributeSelection` meta-filter to module `weka.filters`

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- added `class_index` parameter to `weka.core.converters.load_any_file`
and `weka.core.converters.Loader.load_file`, which allows specifying of
index while loading it (`first`, `second`, `third`, `last-2`, `last-1`,
`last` or 1-based index).
- added `append` and `clear` methods to `weka.filters.MultiFilter` and
`weka.classifiers.MultipleClassifiersCombiner` to make adding of
filters/classifiers easier.
- added `attribute_names()` method to `weka.core.dataset.Instances` class
- added `subset` method to `weka.core.dataset.Instances` class, which returns
a subset of columns and/or rows.

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- added method `list_property_names` to `weka.core.classes` module to allow listing of Bean property names
(which are used by `GridSearch` and `MultiSearch`) for a Java object.

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- Upgraded Weka to 3.9.4
- added method `suggest_package` to the `weka.core.packages` module for suggesting packages for partial class
names/package names (`NNge` or `.ft.`) or exact class names (`weka.classifiers.meta.StackingC`)
- the `JavaObject.new_instance` method now suggests packages (if possible) in case the instantiation fails
due to package not installed or JVM not started with package support

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- method `train_test_split` of the `weka.dataset.Instances` class now creates a copy of itself before
applying randomization, to avoid changing the order of data for subsequent calls.