Abstract :
The data mining is the technique to analyze the complex data. The prediction analysis is the technique which is applied to predict the data according to the input dataset. In the recent times, various techniques have been applied for the prediction analysis. In this paper, k-mean and SVM classifier based prediction analysis technique is improved to increase accuracy and execution time. In the prediction analysis based technique, k-mean clustering algorithm is used to categorize the data and SVM classifier is applied to classify the data. The back propagation algorithm has been applied with the k-mean clustering algorithm to increase accuracy of prediction analysis. The proposed algorithm is implemented in MATLAB and it is been tested that accuracy of clustering is Increased, execution times is reduced for prediction analysis.
By Vimika | Prince Verma"Back Propagated K-Mean Clustering for Prediction of Slow Learners"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017,
URL: http://www.ijtsrd.com/papers/ijtsrd4695.pdf
Paper URL: http://www.ijtsrd.com/engineering/computer-engineering/4695/back-propagated-k-mean-clustering-for-prediction-of-slow-learners/vimika
Keyword :
K-mean; SVM; Prediction; Categorization; Classification.