Breast Cancer is the most prevalent form of cancer and significant reason for high mortality rates among women. Manual diagnosis of this disease requires long hours & specialists. Therefore an Automated breast cancer diagnosis has been developed to reduce the time taken for diagnosis and decreases the spread of cancer. This paper presents a comparative study of four machine learning algorithms namely Logistic Regression, SVM, KNN and Naive Bayes by calculating their classification accuracy, sensitivity, specificity and other parameters. The different hyper-parameters used for different ML algorithms were manually assigned. Among all algorithms, SVM performed better with the accuracy of about 98.24%.


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    Title :

    The Machine Learning based Optimized Prediction Method for Breast Cancer Detection


    Contributors:


    Publication date :

    2020-11-05


    Size :

    842156 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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