Diagnosis Using Data Mining Algorithms for Malignant Breast Cancer Cell Detection

Breast malignant development in the most regular disease among women now a day. Among 2.1 million ladies affecting every year and also furthermore causes the maximum number of cancer death related cases among ladies. Early analysis procedures focus on providing opportune access to malignancy treatment and also decreasing hindrances to care effective diagnosis services. The proposed research work has been primarily focused to contribute to the early analysis of breast malignant growth. Here, a study has been performed on the breast malignant growth. The primary goal of the paper is to locate a subset of features to ensure the patients with malignant and the remaining patients, who face difficulty with bosom malignant has to be prognosticate to envelop those data. The study on various malignant classification approaches using decision tree (DT) and deep learning method are used to find the different time complexity, accuracy, sensitivity, and AUC value.