JJEM: Special Edition 2 (December 2024)
JJEM: Special Edition 2 (December 2024)
2024-12-08
Machine Learning Technique to Identify Breast cancer
Bindu M G, Raghavendra S P
Breast cancer is still among the leading diseases affecting women and there is a high mortality rate for the disease. In this work, the following model of Logistic regression was implemented for diagnosing benign vs malignant tumors of breast cancer using Wisconsin diagnostic dataset. The variables used this dataset's associated with tumor characteristics, such as tumor’s perimeter, smoothness, texture and radius. Hypotheses are examined with the assistance of statistical measures and features are analyzed and depicted in detail to identify significant relationships. As a measure of testing the model, the dataset is divided into the training and the testing dataset. The proposed model (LR) is trained utilizing the training set, and its output is assessed by means of such measures as accuracy, precision and etc. The significance of proper classification of breast cancer is demonstrated in this research while establishing the practicality of the logistic regression technique in achieving it. The outcome exhibit that the proposed system that is logistic Regression can beneficial and reliable diagnostic tool in medical science and beneficial for the improvement of the health status of the individuals suffering from breast tumor additionally for the management of breast tumor.
Breast cancer, logistic regression, benign, malignant, Wisconsin diagnostic dataset, testing, training.