What is new on PyMFE package?

The PyMFE releases are available in PyPI and GitHub.

Version 0.3.0

  • Metafeature extraction with confidence intervals

  • Pydoc fixes and package documentation/code consistency improvements

    • Reformatted ‘model-based’ group metafeature extraction methods arguments to a consistent format (all model-based metafeatures now receive a single mandatory argument ‘dt_model’, and all other arguments are optional arguments from precomputations.) Now it is much easier to use those methods directly without the main class (mfe) filter, if desired.

    • Now accepting user custom arguments in precomputation methods.

    • Added ‘extract_from_model’ MFE method, making easy to extract model-based metafeatures from a pre-fitted model without using the training data.

  • Memory issues

    • Now handling memory errors in precomputations, postcomputations and metafeature extraction as a regular exception.

  • Categorical attributes one-hot encoding option

    • Added option to encode categorical attributes using one-hot encoding instead of the current gray encoding.

  • New nan-resilient summary functions

    • All summary functions now can be calculated ignoring ‘nan’ values, using its nan-resilient version.

  • Online documentation improvement

Version 0.2.0

  • New meta-feature groups

    • Complexity

    • Itemset

    • Concept

  • New feature in MFE to list meta-feature description and references

  • Dev class update

  • Integration, system tests, tests updates

  • Old module reviews

  • Docstring improvement

  • Online documentation improvement

  • Clustering group updated

  • Landmarking group updated

  • Statistical group updated

Version 0.1.1

  • Bugs solved

    • False positive of mypy fixed

    • Contributing link now is working

  • We added a note about how to add a new meta-feature

  • Modified ‘verbosity’ (from ‘extract’ method) argument type from boolean to integer. Now the user can choose the desired level of verbosity. Verbosity = 1 means that a progress bar will be shown during the meta-feature extraction process. Verbosity = 2 maintains all the previous verbose messages (i.e., it logs every “extract” step) plus additional information about the current percentage of progress done so far.

Version 0.1.0

  • Meta-feature groups available

    • Relative landmarking

    • Clustering-based

    • Relative subsampling landmarking

  • Makefile to help developers

  • New Functionalities

    • Now you can list available groups

    • Now you can list available meta-features

  • Documentation

    • New examples

    • New README

  • Bugs

    • Problems in parse categoric meta-features solved

    • Categorization of attributes with constant values solved

  • Test

    • Several new tests added

Version 0.0.3

  • Documentation improvement

  • Setup improvement

  • Meta-feature groups available:

    • Simple

    • Statistical

    • Information-theoretic

    • Model-based

    • Landmarking