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  <titleInfo>
    <title>Data clustering using max-max roughness and its application to cluster patients suspected heart disease</title>
  </titleInfo>
  <name type="personal">
    <namePart>Mohd Amirol Redzuan Mat Rofi</namePart>
    <role>
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    </role>
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  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">my</placeTerm>
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    <place>
      <placeTerm type="text">Kuantan, Pahang</placeTerm>
    </place>
    <publisher>UMP</publisher>
    <dateIssued>2012</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xiii, 128 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM</extent>
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  <abstract>Nowadays, there are many technique to clustering large-scale data. One of the technique to clustering data is using the Rough Set Theory.The objective of this paper is to present the process of Data Clustering Using Maximum-Maximum Roughness and its application to cluster patients suspected heart disease. It is based on clustering techniques based on rough set theory name Max-Max Roughness to describes and employed regarding to solve a classification problem of heart disease patients.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Mohd Amirol Redzuan Mat Rofi</note>
  <note>Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012</note>
  <note>Bibliography: p. 126-128</note>
  <subject authority="lcsh">
    <topic>Cluster analysis</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Data mining</topic>
  </subject>
  <identifier type="isbn">THE0002011(Local)</identifier>
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    <recordCreationDate encoding="marc">121219</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251114204532.0</recordChangeDate>
    <recordIdentifier source="KUKTEM">vtls000067835</recordIdentifier>
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