Creating Ensemble Classifiers with Information Entropy Diversity Measure

Table 3

A list of classification algorithms available by Weka.

Number	Classifier name	Simple description of classifiers
1	Naïve Bayes	The Naïve Bayes classifier using kernel density estimation over multiple values for continuous attributes, instead of assuming a simple normal distribution
2	SMO	Sequential minimal optimization algorithm for training a support vector classifier using polynomial kernels
3	J48	Decision tree, the implementation of C4.5
4	IBk	An instance-based learning algorithm, the implementation of k-nearest neighbor algorithm (kNN)
5	KStar	The K instance-based learner using all nearest neighbors and an entropy-based distance
6	NNge	Nearest neighbor-like algorithm using nonnested generalized exemplars
7	PART	Generating a PART decision list for classification
8	AOD	Perform classification by averaging over all of a small space of alternative Naive Bayes-like models that have weaker independence