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A Review of Common Methods for Pattern Classification Problems
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6.4 Classification Method ASCE for config ASCE mean StDev average CCR Average of ASCE Average of CCR Average of MDL Binomial Response CCR ASCE mean CCR versus classifiers perform Compute Configuration data set deviation of CCR Exec External Validation Feedforward neural network FFN FunNet-BE FunNet-BF FFN V FunNet-BE FNBF-CLS FNBF-MLE functional network model functional networks classifiers graph highest execution highest values input KNN SVM PNN LinDisc 0 KNN Linear Disc Anal linear discriminant analysis Logistic Regression 3.000 LR model matrix MDL versus Average Mean of SSCE mean StDev Logistic mean StDev mean Multinomial Response Nested-Classes Models neural functions neuron nodes output Parameter MDL PNN 0 RBF PNN RBF FFN predictor variables probabilistic neural network radial basis functions RBF FFN FunNet-BE RBFN response variable scatter plots standard deviation StDev Logistic Regression StDev mean StDev support vector machines SVM 0 PNN SVM PNN RBF Table 6.4 Classification Thalassemias training set versus its standard