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Study of K-NN Evaluation for Text Categorization using Multiple Level Learning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 122 - Number 22 |
| Year of Publication: 2015 |
| Authors: Monika, Rajender Singh Chhillar |
10.5120/21855-5151
|
Monika, Rajender Singh Chhillar . Study of K-NN Evaluation for Text Categorization using Multiple Level Learning. International Journal of Computer Applications. 122, 22 ( July 2015), 9-12. DOI=10.5120/21855-5151
Abstract
Predefined category exists for text categorization. In a document, text may be of any type category like government, education or health etc. many methods exist in market invented by researchers for text categorization. One of them is k-NN (k nearest neighbor) algorithm. k play a role to define number of classes for categorization. A training set is generated for each type of category to check its performance than whole text categorized. There is a problem of missing information during training sets. After study recent years invention on k-NN, we find out a solution of this problem. Multiple-Level Learning will improve the performance of k-NN. So in this paper we study about k-NN and propose hybrid algorithm with combination of Multiple-Level Learning and k-NN.
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