IDS572 _Class3 Sept8_2011

IDS572 _Class3 Sept8_2011 - IDS572 Decision Trees September...

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IDS572 Decision Trees September 8, 2011
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Example – Play Tennis? Outlook Tempreature Humidity Windy Class sunny hot high false N sunny hot high true N overcast hot high false P rain mild high false P rain cool normal false P rain cool normal true N overcast cool normal true P sunny mild high false N sunny cool normal false P rain mild normal false P sunny mild normal true P overcast mild high true P overcast hot normal false P rain mild high true N Outlook overcast humidity windy high normal false true sunny rain Not play Not play Play Play Play overcast 2
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Telco churn example 3
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Decision Tree - Characteristics Supervised learning method Hierarchical technique Outcome can be Binary, categorical, or range Parent/child branches Tree depth – how many levels Controlling nodes Splitting rules nominal fields continuous 4
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General Modeling Issues Evaluating performance Training and testing sets Balancing Overfitting Scoring 5
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Decision Tree Methods
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IDS572 _Class3 Sept8_2011 - IDS572 Decision Trees September...

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