Trees

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Unformatted text preview: Classification/Decision Trees (I) Classification/Decision Trees (I) Jia Li Department of Statistics The Pennsylvania State University Email: jiali@stat.psu.edu http://www.stat.psu.edu/jiali Jia Li http://www.stat.psu.edu/jiali Classification/Decision Trees (I) Tree Structured Classifier Reference: Classification and Regression Trees by L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Chapman & Hall, 1984. A Medical Example (CART): Predict high risk patients who will not survive at least 30 days on the basis of the initial 24-hour data. 19 variables are measured during the first 24 hours. These include blood pressure, age, etc. Jia Li http://www.stat.psu.edu/jiali Classification/Decision Trees (I) A tree structure classification rule for the medical example Jia Li http://www.stat.psu.edu/jiali Classification/Decision Trees (I) Denote the feature space by X . The input vector X X contains p features X1 , X2 , ..., Xp , some of which may be categorical. Tree structured classifiers are constructed by repeated splits of subsets of X into two descendant subsets, beginning with X itself. Definitions: node, terminal node (leaf node), parent node, child node. The union of the regions occupied by two child nodes is the region occupied by their parent node. Every leaf node is assigned with a class. A query is associated with class of the leaf node it lands in. Jia Li http://www.stat.psu.edu/jiali Classification/Decision Trees (I) Notation A node is denoted by t. Its left child node is denoted by t...
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This note was uploaded on 02/04/2012 for the course STAT 557 taught by Professor Jiali during the Fall '09 term at Pennsylvania State University, University Park.

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