Back to Search
Start Over
Breast Cancer Classification using the Supervised Learning Algorithms
- Source :
- 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS).
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- Breast cancer (BC) has been the second largest cause of death for women around the world for the past few years. BC is characterized by the chronic pain, genes mutation, color (redness), changes in the size and texture of the skin. BC classification helps clinicians to find a comprehensive and accurate response to treatment, with the most common binary classification (benign / malignant cancer). Nowadays, the Machine Learning (ML) techniques are commonly used in the case of classification of breast cancer. They support with high classification accuracy and rapid evaluation technologies. The proposed research work is mainly focused on supervised learning algorithm, which uses four distinct classifiers: K-Nearest Neighbor (KNN), Weighted K-Nearest Neighbor (WKNN), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Artificial Neural Network (ANN) for the classification of breast cancer. Also, this research work suggests the difference between the aforementioned classifiers and determines their accuracy. The performance of the classifier is assessed based on its accuracy, sensitivity, specificity, precision and recall. Results indicate that, ANN provides the highest accuracy of 97.60% than the other classifiers.
- Subjects :
- Artificial neural network
Computer science
business.industry
Supervised learning
Pattern recognition
medicine.disease
Linear discriminant analysis
Support vector machine
Breast cancer
Binary classification
medicine
Artificial intelligence
Precision and recall
Breast cancer classification
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS)
- Accession number :
- edsair.doi...........da595de1d6785d9a956db5d5c175dc33