Classification Algorithms Based on Template's Decision Rules

In the paper, classification algorithms are presented. These algorithms are based on nondeterministic decision rules that are called template’s decision rules. The conditional part of these rules is a template and the decision part is satisfactorily small set of decisions. Only rules with suficiently large support are used. The proposed classification algorithms were tested on the group of decision tables from the UCI Machine Learning Repository. Results of experiments show that the classification algorithms based on template’s decision rules are often better than the algorithms based on deterministic decision rules.