Waikato/meka
Multi-label classifiers and evaluation procedures using the Weka machine learning framework.
This project provides advanced methods for classifying items that can belong to multiple categories simultaneously. You input a dataset where each item has multiple associated labels, and it helps you build models to predict these multiple labels for new, unseen items. It's designed for data scientists and machine learning engineers working with complex classification tasks.
209 stars.
Use this if you need to build machine learning models for data where each instance can have several categories or tags at the same time, like classifying documents by multiple topics or images by multiple objects.
Not ideal if your data points only ever belong to one category, as simpler single-label classification tools would be more appropriate.
Stars
209
Forks
79
Language
Java
License
GPL-3.0
Category
Last pushed
Jan 22, 2026
Commits (30d)
0
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