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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    Titel :

    The Machine Learning based Optimized Prediction Method for Breast Cancer Detection


    Beteiligte:
    Kumar, Nirdosh (Autor:in) / Sharma, Gaurav (Autor:in) / Bhargava, Lava (Autor:in)


    Erscheinungsdatum :

    2020-11-05


    Format / Umfang :

    842156 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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