Performance Analysis of Data Mining Techniques on Lifestyle Diseases
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Data Mining is the process of knowledge discovery that analyzes the data and create useful patterns from it. A pattern is interesting if it is valid for a given test data and easily understood by humans. The huge amount of data generated for the prediction of lifestyle diseases is too complex and of great size that is difficult to be processed and analyzed by traditional old methods. Advanced Data Mining tools and techniques overcome this problem by discovering hidden patterns and useful information from large and complex data. The aim of the present study is to do the performance analysis of several data mining classification techniques using three different data mining tools over the different lifestyle disease datasets and the data is taken from Indian hospitals and not from UCI repository. In this study, different data mining classification techniques has been conducted on two lifestyle diseases i.e. Heart Disease dataset and Type II Diabetes dataset. The performance analysis is based on the percentage of accuracy and error rate of every applied classification technique. Conclusion: This paper highlights the important role played by data mining tools in analyzing the hidden knowledge from huge volumes of data by using 10 fold cross validation method.
Authors and Affiliations
Divya Sharma, Anand Sharma, Vibhakar Mansotra
Keywords
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