[PDF] COMPARISON OF DIFFERENT DATA MINING ALGORITHMS FOR PREDICTION



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Use of CART and CHAID Algorithms in Karayaka Sheep Breeding

CART and CHAID algorithms of classification and regression trees to predict weaning weight by means of the significant ones among sex, birth type, farm type, birth weight and weighting time in Karayaka sheep MATERIAL and METHODS In this study, to predict weaning weight through CART and CHAID tree-based algorithms, 366 records of Karayaka





Decision Tree: CART

What is CART? Classification And Regression Trees Developed by Breiman, Friedman, Olshen, Stone in early 80’s Introduced tree-based modeling into the statistical mainstream Rigorous approach involving cross-validation to select the optimal tree One of many tree-based modeling techniques CART -- the classic CHAID C5 0



Classification and regression trees

7 Prune the tree with the CART method CHAID15 employs yet another strategy If X is an ordered variable, its data values in the node are split into 10 intervals and one child node is assigned to each interval If X is unordered, one child node is assigned to each value of X Then, CHAID uses significance tests and Bonferroni corrections to



COMPARISON OF DIFFERENT DATA MINING ALGORITHMS FOR PREDICTION

step is more exhaustive than CHAID, by continuing to merge categories of the predictor variable until only two super categories are left The Exhaustive CHAID can find the best split for each predictor variable (Biggs et al , 1991) For regression and classification problems, the tree-based CART, CHAID, and Exhaustive CHAID data



Evaluation of CART, CHAID, and QUEST Algorithms: A Case Study

CART, CHAID, and QUEST, the three commonly used DT algorithms, on project case studies and comprehensive analyzes of rule characteristics and classification results



Decision Tree-based Parametric Analysis of a CNC Turning Process

classification and regression tree (CART) and Chi-squared automatic interaction detection (CHAID) are employed here to investigate the effects of the considered CNC turning parameters on the responses The relative performance of both the algorithms is also compared with respect to solution accuracy and prediction risk



BMC Medical Research Methodology BioMed Central

(based on CART, CHAID and C4 5 methodologies) to cal-culate the probability of hospital mortality and to com-pare these trees with each other, with the classic scores (APACHE II, SAPS II and MPM II-24) and with a model based on multiple logistic regression Methods This is a retrospective study carried out using the database

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