Empirical Evaluation of Classifiers' Performance Using Data Mining Algorithm

Provided by: IJCTT-International Journal of Computer Trends and Technology
Topic: Data Management
Format: PDF
The field of data mining and Knowledge Discovery in Databases (KDD) has been growing in leaps and bounds, and has shown great potential for the future. Data classification is an important task in KDD (knowledge discovery in databases) process. It has several potential applications. The performance of a classifier is strongly dependent on the learning algorithm. In this paper, the authors describe their experiment on data classification considering several classification models. They tabulate the experimental results and present a comparative analysis thereof.

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