Breast cancer is increasing day by day due to life style, hereditary. So, health care need to be modernized it means that the health care data should be properly analyzed. Breast Cancer has become the common cause of death among women. Due to long hours invested in manual diagnosis and lesser diagnostic system available emphasize the development of automated diagnosis for early diagnosis of the disease. Each individual has different values for each attributes of breast cancer. Diagnosis is done by classifying the tumor. Tumors can be either benign or malignant but only latter is the cancer. Malignant are more cancerous than the benign. Unfortunately not all physicians are expert in distinguishing between the benign and malignant. So we need a proper and reliable diagnostic system that can detect the malignant. The frameworks use will provide multipurpose beneficial outputs which includes getting the healthcare data analysis into various forms. In this Smart Health Prediction Using Python, we are proposing a evaluate classification technique used for predicting the risk level of each person. The proposed system is using 13 attributes and 569 datasets to develop an accurate result. The patient risk level is classified using machine learning classification algorithm that is Logistic regression algorithm; the accuracy of the risk level is high when using a greater number of attributes. The proposed system will group together symptoms data and analyze it to provide cumulative information. After the analysis, algorithm could be applied to the resultant and grouping can be made to show a clear result. Our aim is to classify whether the breast cancer is benign or malignant for the analysis purpose of laboratories.

Logistic regression algorithm, Malignant, Benign

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