• DEEPAK RATHORE
• PANKAJ KAWADKAR
• DR. L.K. VISHWAMITRA.

Data mining gives various types of clustering classification algorithm for the various number of applications such as banking, education, medical science, fraud detection, pattern representation, feature extraction for the respective filed etc., there are various data mining algorithms such as supervised learning methods, unsupervised learning methods and semi supervised learning methods for the classification of data. In this article we present the comparative empirical study between the classification methods and measure the performance of both algorithms using some standard evaluation parameters.

Supervised techniques, Neural network, Classifier, Support vector machine, UCI.

"Empirical Study for Classification Ratio using Neural Network and Classification Technique ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.711-714, November-2018, Available :http://www.jetir.org/papers/JETIR1811A91.pdf

"Empirical Study for Classification Ratio using Neural Network and Classification Technique ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp711-714, November-2018, Available at : http://www.jetir.org/papers/JETIR1811A91.pdf