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A Study to Evaluate Different Classifiers on the Basis of Performance of the Prediction for Major Common Diseases

Mohammad Munem Shahriar, Atiqul Islam Chowdhury

Abstract: The world is changing day-by-day. But if there are no human to witness that change, then what the benefit is behind this change. As people are dying from some very common yet risky diseases, people need to be careful from not getting affected by any of those diseases. In this paper, we have worked on common diseases like Lung Cancer, Breast Cancer and Diabetes. They are some of those diseases that are affecting people every day and before preventing the outcome people are dying vigorously. As medical test can be time consuming, the data mining techniques can be very useful. In this study, we have implemented four classifiers on three kinds of datasets of the above mentioned diseases and predicted the performance. From those classifiers, Random Forest has given best results than the rest of the classifiers for the three diseases.

Keywords: medical diseases, predictive data mining, classification, health data, cancer, diabetes

Country: Bangladesh, Subject Area: Data & Knowledge Engineering

Pages: 660 - 663

Edition: Volume 8 Issue 7, July 2019

How to Cite this Article?

Mohammad Munem Shahriar, Atiqul Islam Chowdhury, "A Study to Evaluate Different Classifiers on the Basis of Performance of the Prediction for Major Common Diseases", International Journal of Science and Research (IJSR), https://www.ijsr.net/archive/v8i7/show_abstract.php?id=ART20199345, Volume 8 Issue 7, July 2019, 660 - 663

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