TEXT CATEGORIZATION USING QLEARNING ALOGRITHM
Journal Title: Indian Journal of Computer Science and Engineering - Year 2011, Vol 2, Issue 3
Abstract
This paper aims at creation of an efficient document classification process using reinforcement learning, a branch of machine learning that concerns itself with optimal sequential decision-making. One strength of reinforcement learning is that it provides formalism for measuring the utility of actions that gives benefit only in the future. An effective and flexible classifier learning algorithm is provided, which classifies a set of text documents into a more specific domain like Cricket, Tennis and Football. This novel approach has been evaluated, with standard information retrieval techniques. Recent work in reinforcement learning it has been proved that a quantitative connection between the expected some of rewards of a policy and binary classification performance on a created sub problem. Without any unobservable assumption, the resulting statement is independent of the number of states or actions.
Authors and Affiliations
Dr. S. R. Suresh , T. Karthikeyan , D. B. Shanmugam , J. Dhilipan
Keywords
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