An Analysis Of Breast Cancer Prediction Using Data Mining Techniques

Goh , E-Theng (2010) An Analysis Of Breast Cancer Prediction Using Data Mining Techniques. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Breast cancer is the number one killer decease among women in Malaysia The rate of this d ease keeps increasing for 150-200 cases every year. So, the analysis on the breast cancer is very important. This project main contribution is focus on the analysis on breast cancer prediction with data mining techniques. To fulfill and ease the analysis, the Classification Tool of Breast Cancer Dataset develops for doing the prediction of breast cancer dataset. This project consists of two (2) project methodologies which one for the experiment approach and another one for the classification tool. The classification tool has to build to contribute to the medical field especially researchers of the breast cancer datasets. User can get help with this classification tool to train and test any breast cancer dataset. This classification tool will provided three (3) data mining techniques which is Decision Tree, Naive Bayes and Logistic to predict the outcome of the Breast Cancer dataset. The three (3) classification techniques are chosen because through a lot of literature reviews and case studies, these three (3) techniques are most suitable to predict Breast Cancer dataset and always given high accuracy of outcomes. In future, to obtain more accurate analysis on breast cancer dataset, more data mining techniques are suggested to do prediction on breast cancer dataset.

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