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.
Keywords: Data Mining Evaluation, Statistics,
Visualization, Clustering, Decision Trees, Association
Rules, Neural Networks
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