This monograph presents an extensive survey and comparative study on various clustering and association mining techniques with suitable illustrations. This monograph also reported one new density-based clustering technique EnDBSCAN that can detect embedded cluster structure and OPAM- an efficient one-pass technique for mining frequent item sets. Finally, it discusses medical imaging and the potentials of data mining techniques for analyzing medical imagery. It also proposes an 9.0pt;font-family:"Book Antiqua",serif;mso-bidi-font-family:TimesNewRomanPSMT">architecture for automatic brain cancer detection tool based on Data Mining techniques."> This monograph presents an extensive survey and comparative study on various clustering and association mining techniques with suitable illustrations. This monograph also reported one new density-based clustering technique EnDBSCAN that can detect embedded cluster structure and OPAM- an efficient one-pass technique for mining frequent item sets. Finally, it discusses medical imaging and the potentials of data mining techniques for analyzing medical imagery. It also proposes an 9.0pt;font-family:"Book Antiqua",serif;mso-bidi-font-family:TimesNewRomanPSMT">architecture for automatic brain cancer detection tool based on Data Mining techniques."> This monograph presents an extensive survey and comparative study on various clustering and association mining techniques with suitable illustrations. This monograph also reported one new density-based clustering technique EnDBSCAN that can detect embedded cluster structure and OPAM- an efficient one-pass technique for mining frequent item sets. Finally, it discusses medical imaging and the potentials of data mining techniques for analyzing medical imagery. It also proposes an 9.0pt;font-family:"Book Antiqua",serif;mso-bidi-font-family:TimesNewRomanPSMT">architecture for automatic brain cancer detection tool based on Data Mining techniques."> This monograph presents an extensive survey and comparative study on various clustering and association mining techniques with suitable illustrations. This monograph also reported one new density-based clustering technique EnDBSCAN that can detect embedded cluster structure and OPAM- an efficient one-pass technique for mining frequent item sets. Finally, it discusses medical imaging and the potentials of data mining techniques for analyzing medical imagery. It also proposes an 9.0pt;font-family:"Book Antiqua",serif;mso-bidi-font-family:TimesNewRomanPSMT">architecture for automatic brain cancer detection tool based on Data Mining techniques.">
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