부산대학교 도서관

We conducted research to diagnose breast cancer by classifying malignant and benign tumors. Several machine learning algorithms are used for classification, including Logistic Regression, Decision Trees, and ANN. The aim of this research is to determine the comparison of the three algorithms that have the highest level of accuracy, as well as the parameters and methods for optimizing the training data process in breast cancer classification. This research uses a dataset from Breast Cancer Wisconsin with the Pearson correlation method as feature selection to optimize the dataset for preprocessing data with drop features that have a correlation of more than 0.95. The research results show that the Logistic Regression algorithm is the algorithm that achieves the highest level of accuracy of 97.368421%.