PARAMETERS OPTIMIZATION OF DECISION TREE AND KNN ALGORITHMS FOR BREAST CANCER PREDICTION

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Date

2017

Journal Title

Journal ISSN

Volume Title

Publisher

СДУ хабаршысы - 2017

Abstract

Abstract. Throughout the 20th century, views about breast cancer have drastically changed. Breast cancer is the most common cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2012. This type of cancer is the second most common cancer overall. There is lot of information and data, which give opportunity for analyzing some processes, make some researches in classification and in data mining fields, test some tools of machine learning and make experiments for tuning main methods of supervised learning. Main part of project is creating useful tool for predicting breast cancer with high accuracy before getting ill or in initial stage of disease. This work is fascinating because the goal is to implement a lot of tools for creating web system, which can make effective prediction analysis. In other word, we can anticipate the future for women diseases.

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Keywords

breast cancer, diseases prediction, machine learning methods, scikit, Wisconsin Breast Cancer dataset., СДУ хабаршысы - 2017, №2

Citation

M.M. Meraliyev , K.Ye. Orynbekova , D. Hasanov, M.K. Zhaparov / PARAMETERS OPTIMIZATION OF DECISION TREE AND KNN ALGORITHMS FOR BREAST CANCER PREDICTION / СДУ хабаршысы - 2017