v3102D【初級編D】決定木分析

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K I B M C （CHi-squared Automatic Interaction Detector） N （Classification and Regression Tree） P値 ........................................................................... 39 Q R E F （Quick Unbiased Efficient Statistical Tree） F検定...................................................................8, 71 R2乗値 ....................................................... 87, 89, 90 G IBM SPSS Statisticsによる統計解析 182 数字 D branches..................................................................... 7 CHAID ............................................ 8, 37, 38, 46, 69, 70, 75 CRT / C&R Tree ................. 9, 91, 92, 100, 109, 117, 118, 124, 130 Classification Tree................................................. 10 Data Mining.............................................................. 1 Decision Tree Analysis....................................... 1, 2 Decision Trees........................................................ 18 degree of freedom, df............................................ 25 dependent variable................................................... 3 EX CHAID（Exhaustive CHAID） ............................................................8, 9, 42, 48, 73 Gini ................................................................. 93, 103 2分岐 ..........................................................8, 92, 118 StatsGuild Inc. O P Imbalanced data................................................... 144 independent variable ................................................3 K-Meansクラスター ..............................................9 Machine Learning ....................................................1 multivariate analysis ................................................3 nodes...........................................................................7 over fitting .............................................................. 11 over sampling....................................................... 146 pruning ........................................................... 95, 120 QUEST ................................................................................ 8, 9 Regression Tree ..................................................... 10 root node ....................................................................7