Stock Price Prediction using Rule Based Genetic Algorithm Approach Srinivasan N1,*, Lakshmi C2 1Research Scholar, School of Computing, Sathyabama University, Chennai, Tamil Nadu, India 2Professor, Department of Software Engineering, SRM University, Chennai, Tamil Nadu, India *Corresponding Author E-mail: srinijyothish@gmail.com
Online published on 29 April, 2017. Abstract Securities trade data is a high dimensional time course of action cash related data that positions exceptional computational challenges. Stock data is variable with respect to time, suspecting the future example of the expenses is a trying task. The segments that effect the consistency of stock data can't be judged as the same variables may affect the estimation of the stock always. We propose a data burrowing approach for the desire of the advancement of securities trade. It consolidates using the innate estimation for pre taking care of and a cross breed packing strategy of Hierarchical gathering and Fuzzy C-Means for clustering. The genetic figuring helps in dimensionality diminish and packing makes highlight vectors that help with estimate. Top Keywords Fuzzy, C-Means, Stock, Prediction, Genetic Algorithm. Top |