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Study of Data Mining Algorithms in the Context of Performance Enhancement of Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 134 - Number 9 |
| Year of Publication: 2016 |
| Authors: Aditi Goel, Saurabh Kr. Srivastava |
10.5120/ijca2016907963
|
Aditi Goel, Saurabh Kr. Srivastava . Study of Data Mining Algorithms in the Context of Performance Enhancement of Classification. International Journal of Computer Applications. 134, 9 ( January 2016), 1-5. DOI=10.5120/ijca2016907963
Abstract
Data mining can help researchers to gain novel and deep insights for understanding of large datasets. Nowadays, people are using data mining algorithms in different contexts like banking, hospitals, marketing etc. Classification algorithm plays a vital role. In the study, we found that SVM is the best classifier amongst all the classifiers. Here we used learning algorithms with the historical dataset to train the classifier and the test samples are used to validate the correctness of the classifier. We might have structured semi-structured and unstructured datasets which are used for classification. We have performed the study of reputed literatures that belong to classification area to identify some new enhancements in the classifiers. A few most important classifiers are SVM, decision tree, neural network, Naive Bayes. We found most of the literatures were concentrated on SVM classifier so we targeted SVM classifier for the performance enhancement. SVM are important tool in data-mining to classify data. The aim of this review is to identify the effectiveness of kernel parameters for classification of data using Support Vector.
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