The technique that is utilized for analyzing the complex data is known as data mining technique. As per the input dataset provided, the predictions are made for the data with the help of prediction analysis method. There are various new techniques proposed for the execution of prediction analysis technique. In this paper, the k-mean algorithm is utilized for categorizing the data. Further, for the classification of this data, the SVM classifier is applied. For improving the performance of prediction analysis in terms of accuracy the back propagation algorithm is used along with the k-mean clustering algorithm. For executing this proposed technique, the MATLAB tool is used. As per the experimental results it is concluded that the accuracy of the clustering algorithm is improved as well as the execution time utilized for prediction analysis is decreased.

The data mining is the technology which is applied to extract the useful information from the rouge information. The clustering is the efficient technique which is applied to cluster the similar and dissimilar type of data. The prediction analysis is applied in which technique of clustering is applied which will cluster the data and in the second step technique of classification is applied which will classify the similar and dissimilar type of data. In this paper, various technique of prediction analysis is reviewed and discussed in terms of various parameters