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            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: Implementation",
            "Topic :: Software Development :: Libraries"
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        "description": "# Feature Selector: Simple Feature Selection in Python\n\nFeature selector is a tool for dimensionality reduction of machine learning datasets.\n---\n\n# Install\n```\npip install feature_selector\n```\n\n# Methods\n\nThere are five methods used to identify features to remove:\n\n1. Missing Values\n2. Single Unique Values\n3. Collinear Features\n4. Zero Importance Features\n5. Low Importance Features \n\n## Usage\n\nRefer to the [Feature Selector Usage notebook](https://github.com/WillKoehrsen/feature-selector/blob/master/Feature%20Selector%20Usage.ipynb) for how to use\n\n## Visualizations\n\nThe `FeatureSelector` also includes a number of visualization methods to inspect \ncharacteristics of a dataset. \n\n__Correlation Heatmap__\n\n![](images/example_collinear_heatmap.png)\n\n__Most Important Features__\n\n![](images/example_top_feature_importances.png)\n\nRequires:\n\n```\npython==3.6+\nlightgbm==2.1.1\nmatplotlib==2.1.2\nseaborn==0.8.1\nnumpy==1.14.5\npandas==0.23.1\nscikit-learn==0.19.1\n\n```\n\n## Contact\n\nAny questions can be directed to wjk68@case.edu!\n\n\n",
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        "keywords": "\u7279\u5f81\u9009\u62e9,Feature Selector,Feature",
        "license": "MIT",
        "maintainer": "JieYuan",
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        "name": "feature-selector",
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        "summary": "FeatureSelector is a class for removing features for a dataset intended for machine learning",
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