Prediction of investment in share Market using fuzzy fast Classification

Abstract

Data mining has gained more attention in the information industry newlinedue to the wide availability of enormous amount of data and the need for newlinetuning such data into useful information and knowledge Several techniques newlinehave been used in data mining for knowledge discovery The proposed newlineclassification technique is used to classify share market dataset with an newlineincreased accuracy and speed newlineThe goal of classification is to accurately predict the target class for newlineeach class in the dataset where the class assignments are already known The newlinebasic type of classification is binary classification In binary classification the newlinetarget attribute has only two possible class say low or high Classification has newlinebeen recently used in most applications and their use in classifying share newlinemarket helps the investor to predict the shares which had the highest and newlinelowest rating in the market so that they can invest safely for highest profit newlinereturn newlineShare market is one of the biggest as well as smallest investment setup newlinefor higher middle and lower class people and the investment is based upon newlineones capability and availability of the funds they are holding They can invest newlinefrom one rupee to more than thousand rupees for a share However newlineinvestment is not a problem but gaining profit is more important So it is newlinealways necessary for the investors to know which company yields a better newlineprofit at the time of investment newline