A New Approach for Evaluation of Data Mining Techniques

This paper tries to put a new direction for the evaluation of some techniques for solving data mining tasks such as: Statistics, Visualization, Clustering, Decision Trees, Association Rules and Neural Networks. The new approach has succeed in defining some new criteria for the evaluation process, and it has obtained valuable results based on what the technique is, the environment of using each techniques, the advantages and disadvantages of each technique, the consequences of choosing any of these techniques to extract hidden predictive information from large databases, and the methods of implementation of each technique. Finally, the paper has presented some valuable recommendations in this field.