Certain investigations on multilevel Fuzzy coherent rule and tree Mining

Abstract

Datamining and Machinelearning techniques have been developed to newlineturn data into useful knowledge Association rule mining clustering newlineclassification and prediction are the some of the widely used techniques in newlinedata mining The above techniques are used in binary data spatial and newlinetemporal data set for mining task oriented knowledge Most of the algorithms newlinefor mining association rules identify relationships among transactions using newlinebinary values and mine rules at a singleconcept level or multiple levels newlineFuzzy association rule mining was developed to mine rules in quantitative newlinetransactions that occurs both in single and multiple levels. Mining newlineassociations among itemsets that use support and confidence thresholds at newlinedifferent levels of hierarchical data would not give interesting rules both for newlinebinary or quantitative data So techniques using multiple support and newlineconfidence thresholds are invented to solve the above problem newline newline