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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
Breast cancer is a critical disease witnessed among women. Owing to the high number of features, predicting the breast cancer using the digital method is increasingly challenging. To predict the breast cancer accurately and efficiently, this work has proposed the feature selection based technique coupled with the dimension reduction technique for the efficient prediction of breast cancer. Results collected and analyzed before applying the feature selection technique and after feature selection technique. Experiment highlighted that the KNN based machine learning algorithm with Extra Tree based feature selection method proved to be extremely effective in terms of performance. Computation time recording during the experimentation is also presented to measure the time gain received before and after the proposed approach. Proposed technique will be able to predict the breast cancer with the higher degree of accuracy, at the same time, prediction time needed would decline subsequently. Therefore, proposed approach will greatly aid the medical staff in confirming the breast cancer.
Keyword
Breast cancer, machine learning in breast cancer, feature selection in breast cancer, recall score in breast cancer
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