Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework using Matlab

Abstract

Data privacy protection is one of the most disturbed issues on the present industry Data isolation issue require to be addressed immediately previous to the data sets are common on a cloud. Data point refers to as hiding compound data for owner of data records. Expand the process of analysis over big multidimensional information as well, by importance open problems and real investigate trends. In this research new algorithm called Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework is been implemented on mat lab. Dispensation great quantity of information is attractive a confronting for data investigation software. Data clustering is a documented information study technique in data mining while adaptive K-Means is the well known partition clustering method. The inspiration at the back ACMDDA proposing algorithm is to contract with different dimensional information clustering, with minimum amount error rate and utmost meeting rate. With the help of multidimensional data set of map dipping framework, here implemented algorithm will amplify the competence of the big data for out system.