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Jhumi Thapa, Anshu Ghimire
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- Assistant Professor, Assistant Professor, Department of Computer Science and Engineering1,2 Nepal Engineering College, Department of Computer Science and Engineering1,2 Nepal Engineering College, Bhaktapur, Bhaktapur, Nepal, Nepal
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Abstract
nBreast Cancer is the most common type of cancer seen in women on present days, which is also considered as life threating disease. If this cancer can be detected on its early stage it can be life saver for many people around the world. Machine Learning techniques has become one of the hotspots for predicting early diagnosis of breast cancer. This research work experiments with the two most popularly used Supervised Machine Learning Algorithms, K-Nearest Neighbor, and Artificial Neural Network which will detect breast cancer by training its attributes and to find out the most effective with respect to confusion matrix, accuracy, and precision. The findings indicate that the Artificial Neural Network Machine achieved superior performance, outperforming all other classifiers with an accuracy rate of 98%. All the work are done on python programming language using Scikit-learn library and tensor flow.
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Keywords: K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), breast cancer, machine learning, prediction, Fine Needle Aspirate (FNA)
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Artificial Intelligence Research & Advances(joaira)]
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References
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Journal of Artificial Intelligence Research & Advances
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| Volume | 11 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | January 14, 2024 | |
| Accepted | April 9, 2024 | |
| Published | April 24, 2024 |
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