Global Optimization Ensemble Model for Classification Methods

Table 5

Data set and suitable classifiers.

Dataset	Classifier	Capabilities
All datasets	K-NN	Polynomial, numerical, binomial attributes, and labels can handle missing values
All datasets	Decision tree	Polynomial, numerical, and binomial attributes cannot handle numeric labels and can handle missing values
Heart, wine, and educational and sonar dataset	Rule induction
Cancer, heart, adult income dataset	ID3	Can only handle binomial and polynomial labels and attributes and cannot handle missing values
All datasets	W-AODE
All datasets	W-Prism
Educational progress and sonar and adult income dataset	Random forest	Polynomial, numerical, and binomial attributes cannot handle numeric labels and cannot handle missing values
All datasets	W-PART
All datasets	W-J48
Sonar, diabetes, cancer, andadult income dataset	Logistic regression	Numerical attributes and binomial labels cannot handle missing values