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Table 3 Adjusting modeling parameters

From: Personality classification based on profiles of social networks’ users and the five-factor model of personality

Setting parameters Model Abbreviations
Naïve Bayes NB
Index split = 4 Decision tree DT
Level of confidence for pruning = 0.25
Minimum number of samples in each leaf = 2
The maximum depth of the tree = 50
The number of hidden layers = 1 Neural network ANN
Learning rate = 0.3
Momentum rate = 0.2
Number of training cycles = 300
Core rate =  X*Y  Support vector machine SVM
Constant = 0
The number of repetitions = 10 Ada boost-Naïve Bayes Ada-NB
The number of repetitions = 10 Ada boost-decision tree Ada-DT
The number of repetitions = 10 Ada boost-neural network Ada-NN
The number of repetitions = 10 Ada boost-support vector machine Ada-SVM