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Data Mining With Decision Trees

MSCS282 - Data Mining With Decision Trees. 2. Overview. Decision TreesRules and Language BiasConstructing Decision TreesSome AnalysesHeuristicsQuality AssessmentExtensions. MSCS282 - Data Mining With Decision Trees. 3. Goals. Explore the complete data mining processUnderstand decision trees a

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Data Mining With Decision Trees

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    1. Data Mining With Decision Trees Craig A. Struble, Ph.D. Marquette University

    2. MSCS282 - Data Mining With Decision Trees 2 Overview Decision Trees Rules and Language Bias Constructing Decision Trees Some Analyses Heuristics Quality Assessment Extensions

    3. MSCS282 - Data Mining With Decision Trees 3 Goals Explore the complete data mining process Understand decision trees as a model Understand how to construct a decision tree Recognize the language bias, search bias, and overfitting avoidance bias for decision trees Be able to assess the performance of decision trees

    4. MSCS282 - Data Mining With Decision Trees 4 Decision Trees A graph (tree) based model used primarily for classification Extensively studied Quinlan is the primary contributor to the field Applications are wide ranging Data mining Aircraft flying Medical diagnosis Etc.

    5. MSCS282 - Data Mining With Decision Trees 5 Decision Trees

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