Machine Learning Algorithms in Web Page Classification

A  Rama  and B  Nagalakshmi

doi:10.17485/ijst/2015/v8i31/88974

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Machine Learning Algorithms in Web Page Classification

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i31/88974

Year: 2015, Volume: 8, Issue: 31, Pages: 1-5

Original Article

Machine Learning Algorithms in Web Page Classification

A. Rama^* and B. Nagalakshmi

Department of Computer Science, Bharath University, Chennai - 600073, Tamil Nadu, India;
[email protected], nagalakshmib.cse.bharathuniv.ac.in

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In this paper we tend to use machine learning algorithms like SVM, KNN and GIS to perform a behavior comparison on the net pages classifications drawback, from the experiment we tend to see within the SVM with tiny range of negative documents to make the centroids has the littlest storage demand and also the least on line take a look at computation value. However most GIS with completely different range of nearest neighbors have a fair higher storage demand and on line take a look at computation value than KNN. This means that some future work ought to be done to do to cut back the storage demand and on list take a look at value of GIS.
Keywords: Net Classifications, Machine Learning, LIBSVM, SVM, K-NN