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15.062 Data Mining – Spring 2003 Nitin R. Patel Comparison of Data Mining techniques – large data sets – Guidelines (… and only guidelines) H: high, M:medium, L:low. Neural Nets Trees k-Nearest Neighbors Accuracy Logistic Discriminant Naïve Multiple Regression Analysis Bayes Linear Regression M M M HM H M HM Intepretability H H M H L H L SpeedTraining H H H HM L HM H SpeedDeployment H H H H H HM L Effort in choice and transformation of indep.Vars. Effort to tune performance parameters Robustness to Outliers in indep vars Robustness to irrelevant variables Ease of handling of missing values Natural handling both categorical and continuous variables HM HM HM HM L L ML L L L ML H ML ML ML ML ML ML HM H HM H H HM H L ML L M M M H M H ML H H ML M H H L