Predicting Breast Cancer using Modern Data Science Methodology
Vinoothna Manohar Botcha1, Bhanu Prakash Kolla2
1Vinoothna Manohar Botcha, (Correspondence Author) Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
2Bhanu Prakash Kolla, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 20 August 2019 | Manuscript published on 30 August 2019 | PP: 4444-4446 | Volume-8 Issue-10, August 2019 | Retrieval Number: J10770881019/2019©BEIESP | DOI: 10.35940/ijitee.J1077.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Breast Cancer is the mass occurring cancer in women according to the World Health Organization(WHO), But the early prediction of breast cancer helps in the recovery for the effected one’s. Reasons for breast cancer were Hormone replacement therapy or getting explore to harmful radioactive rays and due to late childbearing. The aim is to diagnose cancer by using a machine learning technique, Random Forest, for accurate solutions. The dataset we used is the Wisconsin Breast Cancer dataset. The output which the error rate was only about “0.0177”.
Keywords: Breast Cancer Prediction. Machine Learning, Data Science, Random Forest.
Scope of the Article: Regression and Prediction