Two new feature selection methods based on learn-heuristic techniques for breast cancer prediction: a comprehensive analysis
K Karimi, A Ghodratnama… - Annals of Operations …, 2023 - Springer
… feature selection (FS) methods based upon an imperialist competitive algorithm (ICA) and a
bat algorithm … performed on the Wisconsin diagnostic breast cancer (WDBC) dataset. Results …
bat algorithm … performed on the Wisconsin diagnostic breast cancer (WDBC) dataset. Results …
A two-stage feature selection approach using hybrid quasi-opposition self-adaptive coati optimization algorithm for breast cancer classification
K Thirumoorthy - Applied Soft Computing, 2023 - Elsevier
… feature selection ratio. We used the three benchmark datasets (Breast Cancer Wisconsin
Diagnostic Dataset (… They used WDBC dataset for cancer classification. They compared the GA …
Diagnostic Dataset (… They used WDBC dataset for cancer classification. They compared the GA …
[PDF][PDF] Breast Cancer Detection Improvement by Grasshopper Optimization Algorithm and Classification SVM.
AE Rahmani, M Katouli - Revue d'Intelligence Artificielle, 2020 - researchgate.net
… In this study, binary Bat algorithm was used. The accuracy of the proposed … Modified bat
algorithm for feature selection with the wisconsin diagnosis breast cancer (WDBC) dataset…
algorithm for feature selection with the wisconsin diagnosis breast cancer (WDBC) dataset…
Breast cancer detection based on modified Harris Hawks optimization and extreme learning machine embedded with feature weighting
F Jiang, Q Zhu, T Tian - Neural Processing Letters, 2023 - Springer
… on Wisconsin Diagnosis Breast Cancer (WDBC) data set. The … features out and abandons
lower relevant features, then a subset of original data set will be obtained after feature selection…
lower relevant features, then a subset of original data set will be obtained after feature selection…
Breast cancer diagnosis based on hybrid rule-based feature selection with deep learning algorithm
… feature selection helps in key attributes that are relevant to the diagnosis of breast cancer.
The model has been tested utilizing the well-known Wisconsin Breast Cancer Dataset (WBCD…
The model has been tested utilizing the well-known Wisconsin Breast Cancer Dataset (WBCD…
Optimizing feature selection and parameter tuning for breast cancer detection using hybrid GAHBA-DNN framework
K Kamala Devi, J Raja Sekar - Journal of Intelligent & Fuzzy Systems - content.iospress.com
… for utilizing the Wisconsin breast cancer datasets and SEER datasets for the best … [11]
created a bat algorithm for feature selection and tested it on the WDBC dataset. They found that …
created a bat algorithm for feature selection and tested it on the WDBC dataset. They found that …
… mutation enhanced elephant herding optimization (Ameho) based feature selection and kernel extreme learning machine (Kelm) classifier for breast cancer diagnosis
RSP Priya - Turkish Journal of Computer and Mathematics …, 2021 - turcomat.org
… This paper reports feature selection and classification method for breast cancer … Modified
bat algorithm for feature selection with the wisconsin diagnosis breast cancer (WDBC) dataset…
bat algorithm for feature selection with the wisconsin diagnosis breast cancer (WDBC) dataset…
[HTML][HTML] Optimal feature selection using binary teaching learning based optimization algorithm
M Allam, M Nandhini - Journal of King Saud University-Computer and …, 2022 - Elsevier
… of features on Wisconsin diagnosis breast cancer (WDBC) … process as a wrapper technique
based on Bat Algorithm (BA) … modification of TLBO to search the solution space of features …
based on Bat Algorithm (BA) … modification of TLBO to search the solution space of features …
A composite hybrid feature selection learning-based optimization of genetic algorithm for breast cancer detection
… for Wisconsin Diagnostic Breast Cancer (WDBC), wine, and zoo … diagnosis of Breast cancer
disease by using a benchmark dataset on our proposed composed hybrid feature selection (…
disease by using a benchmark dataset on our proposed composed hybrid feature selection (…
[HTML][HTML] An enhancement in cancer classification accuracy using a two-step feature selection method based on artificial neural networks with 15 neurons
MA Rahman, RC Muniyandi - Symmetry, 2020 - mdpi.com
… the cancer. This research utilized the benchmark Wisconsin Diagnostic Breast Cancer (WDBC)
dataset … [21] utilized a modified bat algorithm (MBA) to select the optimal features from the …
dataset … [21] utilized a modified bat algorithm (MBA) to select the optimal features from the …