Oct 16, 2019 · In this paper, the GWOs and SVM were used for feature selection and data classification in order to increase the accuracy of breast cancer ...
Application of the proposed method increased the improvement of the evaluated criteria, which increased the accuracy of diagnosis by 27.68%, compared to former ...
Oct 16, 2019 · In this paper, the GWOs and SVM were used for feature selection and data classification in order to increase the accuracy of breast cancer ...
Application of the proposed method increased the improvement of the evaluated criteria, which increased the accuracy of diagnosis by 27.68%, compared to former ...
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May 10, 2024 · This hybrid approach aims to enhance the accuracy of breast cancer classification by determining the optimal Support Vector Machine parameters.
The first contribution is improving the performance of support vector machine (SVM) using a recent grey wolf optimizer (GWO) for diagnosis breast cancer with ...
May 10, 2024 · This hybrid approach aims to enhance the accuracy of breast cancer classification by determining the optimal Support Vector Machine parameters.
Missing: best | Show results with:best
... Improving the performance of support-vector machine by selecting the best features by Gray Wolf algorithm to increase the accuracy of diagnosis of breast cancer ...
Improving the performance of support-vector machine by selecting the best features by Gray Wolf algorithm to increase the accuracy of diagnosis of breast cancer.
This study examines the use of support vector machine (SVM) learning algorithms in predictive analytics models for the detection of breast cancer. This study ...