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Two-step Technique for Prediction Analysis using K-Means Clustering Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 166 - Number 9 |
| Year of Publication: 2017 |
| Authors: Shalu Saxena, Pankaj Kumar, Raj Gaurang Tewari |
10.5120/ijca2017914110
|
Shalu Saxena, Pankaj Kumar, Raj Gaurang Tewari . Two-step Technique for Prediction Analysis using K-Means Clustering Algorithm. International Journal of Computer Applications. 166, 9 ( May 2017), 9-12. DOI=10.5120/ijca2017914110
Abstract
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.
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