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Prediction of Regional Disease Using Data Mining Techniques

File Size:
1.38 MB
Volume:
Volume 4, Issue 6 (June, 2018)
Publication No:
IJTC201806001
Author:
Rupinder Kaur Gurm, Navjot Kaur
Downloads:
11 x

Abstract:
Data mining techniques are useful in medical science to analysis medical data and diseases contents. The regional disease like heart disease. The heart disease is the main cause of death worldwide. It is a very complex task to predict the disease like heart disease because it requires more knowledge and experience. In the medical sector contains lots of hidden information that is used in making decisions. 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 the base paper, neural network technique is applied for the prediction analysis. In the technique whole data is divided into testing and training part. The test data is classified into two classes’ means first class is of data which have regional disease and second which does not have regional disease. In this research work, further improved will be proposed in this existing method using back propagation algorithm. The proposed improvement increase accuracy of classification and reduce execution time. Data mining provide methodology and technology for making a decision. Data mining techniques will result a quick prediction of disease with high accuracy. Data mining is an advanced technology.

Keyword:
Data Mining, Classification, Clustering, Regional disease (heart disease), SVM, KNN.