IDENTIFICATION OF PATIENTS WITH BREAST CANCER BY USING MACHINE LEARNING ALGORITHMS OVER SCIKIT-LEARN ML FRAMEWORK

Shamiluulu, Sh. (2016) IDENTIFICATION OF PATIENTS WITH BREAST CANCER BY USING MACHINE LEARNING ALGORITHMS OVER SCIKIT-LEARN ML FRAMEWORK. Scientific-Practical Journal of Medicine, "Vestnik KazNMU" (4). ISSN 2524 - 0692

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IDENTIFICATION OF PATIENTS WITH BREAST CANCER BY USING MACHINE LEARNING ALGORITHMS OVER SCIKIT-LEARN ML FRAMEWORK.pdf

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Abstract

In this research study the effect of normalization techniques is examined. The five different supervised machine learning algorithms i.e., KNN, Decision tree, Naïve-base, Logistic regression and ANN are used on breast cancer dataset obtained from UCI machine learning repository and their performances are compared. The study reveal that different preprocessing techniques can increase the classification accuracy over 90% where high performance is given to Logistic regression and ANN. The proposed approach can be implemented in a well-known benchmark medical problem with real clinical data forbreast cancer disease diagnosis.

Item Type: Article
Uncontrolled Keywords: Breast cancer, Machine Learning Algorithms, Data Classification, Computer Aided Prognosis and Diagnosis
Subjects: Материалы семинаров и конференций > Материалы семинаров и конференций КазНМУ
Divisions: Научно-практический журнал "Вестник КазНМУ" > Выпуск №4 2016 год
Depositing User: Mr Askhat Zhakaev
Date Deposited: 06 Jun 2018 11:09
Last Modified: 06 Jun 2018 11:09
URI: http://repository.kaznmu.kz/id/eprint/15129

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