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Feature selector is a tool for dimensionality reduction of machine learning datasets
| Date | Stars |
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| 2026-07-31 | 2230 |
| 2026-08-05 | 2230 |
| 2026-08-06 | 2230 |
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# Feature Selector: Simple Feature Selection in Python Feature selector is a tool for dimensionality reduction of machine learning datasets. # Methods There are five methods used to identify features to remove: 1. Missing Values 2. Single Unique Values 3. Collinear Features 4. Zero Importance Features 5. Low Importance Features ## Usage Refer to the [Feature Selector Usage notebook](https://github.com/WillKoehrsen/feature-selector/blob/master/Feature%20Selector%20Usage.ipynb) for how to use ## Visualizations The `FeatureSelector` also includes a number of visualization methods to inspect characteristics of a dataset. __Correlation Heatmap__  __Most Important Features__  Requires: ``` python==3.6+ lightgbm==2.1.1 matplotlib==2.1.2 seaborn==0.8.1 numpy==1.22.0 pandas==0.23.1 scikit-learn==0.19.1 ``` ## Contact Any questions can be directed to [email protected]!
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Will Koehrsen · @gridstatus · Israel
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Darigov Research
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e4d5fefa26f4591a, desc:datasets