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  <titleInfo>
    <title>Feature engineering and selection</title>
    <subTitle>a practical approach for predictive models</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Kuhn, Max.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Johnson, Kjell.</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">bibliography</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">flu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Boca Raton</placeTerm>
    </place>
    <publisher>CRC Press, Taylor &amp; Francis Group</publisher>
    <dateIssued>c2020</dateIssued>
    <dateIssued encoding="marc">2020</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xv, 297 p. : ill.</extent>
  </physicalDescription>
  <abstract>The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for finding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.</abstract>
  <tableOfContents>Illustrative example: predicting risk of ischemic stroke -- A review of the predictive modeling process -- Exploratory visualizations -- Encoding categorical predictors -- Engineering numeric predictors -- Detecting interaction effects -- Handling missing data -- Working with profile data -- Feature selection overview -- Greedy search methods -- Global search methods.</tableOfContents>
  <note type="statement of responsibility">Max Kuhn, Kjell Johnson.</note>
  <note>Includes bibliographical references and index.</note>
  <subject>
    <topic>Predictive control</topic>
    <topic>Data processing</topic>
  </subject>
  <subject>
    <topic>Predictive control</topic>
    <topic>Mathematical models</topic>
  </subject>
  <subject>
    <topic>R (Computer program language)</topic>
  </subject>
  <classification authority="lcc">TJ217.6 .K84 2020</classification>
  <relatedItem type="series">
    <titleInfo>
      <title>Chapman &amp; Hall/CRC data science series</title>
    </titleInfo>
  </relatedItem>
  <identifier type="isbn">1138079227</identifier>
  <identifier type="isbn">9781138079229</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">210114</recordCreationDate>
    <recordIdentifier source="OCoLC">on1099869989</recordIdentifier>
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