AutoViML/featurewiz_polars
New Polars implementation of the classic featurewiz MRMR algorithm. Created by Ram Seshadri. Collaborators welcome.
This tool helps data scientists and machine learning engineers prepare large datasets for model building. It automatically creates and selects the most relevant features from your raw data, producing a cleaner, more focused dataset ready for training. This significantly speeds up the data preparation phase, especially for those working with extensive datasets.
No commits in the last 6 months. Available on PyPI.
Use this if you need to quickly and efficiently select the best features from a large dataset to build robust machine learning models.
Not ideal if you prefer manual, fine-grained control over every step of feature engineering and selection or if your datasets are very small.
Stars
47
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 30, 2025
Commits (30d)
0
Dependencies
8
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