dataclr/dataclr
Feature selection for tabular datasets using advanced filter and wrapper methods
When building predictive models from large tables of data, it's often hard to know which columns (features) are most important. This tool helps data scientists and machine learning engineers intelligently identify the most impactful features from their raw tabular datasets. You input your raw data and a predictive model, and it outputs a prioritized list of the most relevant features, improving your model's accuracy and simplicity.
No commits in the last 6 months. Available on PyPI.
Use this if you are a data scientist or ML engineer struggling to select the best features from a complex tabular dataset for your classification or regression models.
Not ideal if you are working with unstructured data like images, text, or audio, or if you need a simple, manual feature selection method.
Stars
20
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 09, 2025
Commits (30d)
0
Dependencies
12
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