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RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers

Nicola Lazzarini; Jaume Bacardit


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    "description": "<p>RGIFE is a feature reduction heuristic for the identification of small panels of highly predictive biomarkers. The heuristic is based on an <strong>iterative reduction paradigm</strong>: first train a classifier, then rank the attributes based on their importance and finally remove attributes in block. RGIFE is designed to work with large-scale datasets and identifies reduced set of attributes with high classification power.</p>", 
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    "title": "RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers", 
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    "keywords": [
      "biomarkers", 
      "feature selection", 
      "omics", 
      "classification", 
      "machine learning"
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    "publication_date": "2016-12-06", 
    "creators": [
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        "affiliation": "Newcastle University", 
        "name": "Nicola Lazzarini"
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        "affiliation": "Newcastle University", 
        "name": "Jaume Bacardit"
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