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Download PDFOpen PDF in browserBreast Cancer Classification Using Logistic RegressionEasyChair Preprint 106836 pages•Date: August 7, 2023AbstractBreast cancer is a prevalent disease among women, and early detection plays a vital role in effective treatment. In this study, a logistic regression model is developed to classify breast tumors as benign or malignant. The Wisconsin Diagnostic Breast Cancer dataset is utilized, consisting of various features related to tumor characteristics. The dataset is explored, visualized, and divided into training and testing sets. A logistic regression model is trained and evaluated using accuracy metrics. Finally, the trained model is used to predict the malignancy of a given breast tumor. This study highlights the importance of accurate breast cancer classification and demonstrates the efficacy of logistic regression in achieving this goal. Keyphrases: Classification, breast cancer, data exploration, data visualization, logistic regression Download PDFOpen PDF in browser |
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