z-logo
open-access-imgOpen Access
Two-step Technique for Prediction Analysis using K-Means Clustering Algorithm
Author(s) -
Shalu Saxena,
Pankaj Kumar,
Raj Gaurang
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017914110
Subject(s) - computer science , cluster analysis , algorithm , data mining , artificial intelligence
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 content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom