A New Approach For Classification Algorithm In Data Mining

• Author(s): M. Thillaikarasi
• Paper ID: 1700077
• Page: 77-82
• Published Date: 31-10-2017
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 1 Issue 4 October-2017

Abstract

Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information, which is collected and assembled in common areas, such as data warehouses, for efficient analysis, data mining algorithms, facilitating business decision making and other information requirements to ultimately cut costs and increase revenue. I consider classification techniques that are based on statistical and AI techniques to perform controlled experiment data characteristics are systematically altered to introduce imperfections such as nonlinearity, unequal covariance. Two machine learning algorithms Naive Bayes and Support Vector Machine (SVM) is used to build models for the automatic classification of the tweets, and these models were evaluated across the metrics of accuracy, precision, recall, area under curve and measure. The results reveal that the proposed sampling strategy makes more judicious use of data points by selecting locations that clarify high level structures in data, rather than choosing points that merely improve quality of function approximation.

Keywords

Data Mining, Knowledge discovery data base, Decision tree, Extreme learning machine, Support Vector Machine

Citations

IRE Journals:
M. Thillaikarasi "A New Approach For Classification Algorithm In Data Mining" Iconic Research And Engineering Journals Volume 1 Issue 4 2017 Page 77-82

IEEE:
M. Thillaikarasi "A New Approach For Classification Algorithm In Data Mining" Iconic Research And Engineering Journals, 1(4)