Comparison of Linear and Robust Discriminant Analysis Methods in the Classification of Malignant and Benign Breast Cancer
DOI:
https://doi.org/10.24252/msa.v13i2.59043Keywords:
Breast Cancer, Discriminant Analysis, WomenAbstract
Breast cancer is one of the most common types of cancer in women worldwide. According to data from the World Health Organization (WHO), breast cancer accounts for about 25% of all cancer cases in women. Early diagnosis has a very important role in determining the patient's survival rate. The purpose of this study is to determine which method is more effective in classifying breast cancer. The methods used in this study are using linear discriminant analysis and robust discriminant. The results showed that the proportion of errors using linear discriminant analysis was 3, 34% while the proportion of errors using robust discriminant analysis was 12, 3% so it can be concluded that the linear discriminant analysis method is more effective in classifying malignant and benign breast cancer.
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