Comparative Analysis of Different Classifiers for the Wisconsin Breast Cancer Dataset

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"Comparative Analysis of Different Classifiers for the Wisconsin Breast Cancer Dataset"
written by Leena Vig,
published by Open Access Library Journal, Vol.1 No.6, 2014

has been cited by the following article(s):

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[7]	PENERAPAN TEKNIK KOMBINASI OVERSAMPLING DAN UNDERSAMPLING UNTUK MENGATASI PERMASALAHAN IMBALANCED DATASET
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[8]	Deep Learning Hybrid with Binary Dragonfly Feature Selection for the Wisconsin Breast Cancer Dataset
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[9]	Breast Cancer Detection with Revamped Dataset Using Machine Learning Techniques
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[10]	Machine Learning Approach for Breast Cancer Early Diagnosis
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[11]	Efficient Role of Machine Learning Classifiers in the Prediction and Detection of Breast Cancer
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[12]	Analysis of Machine Learning Algorithms on Cancer Dataset
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[13]	Application of decision tree-based ensemble learning in the classification of breast cancer
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[14]	Comparative Study of Machine Learning Algorithms Using the Breast Cancer Dataset
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[15]	Classification of Breast Lesions using Modified Masood Score and Neural Network
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[16]	Comparison of machine learning techniques to predict cardiovascular disease
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[17]	HUMAN DISEASE DETECTION USING ARTIFICIAL INTELLIGENCE

[1]	The application of machine learning in 3D/4D printed stimuli-responsive hydrogels Advances in Colloid and Interface Science, 2025 DOI:10.1016/j.cis.2024.103360

[2]	Deep learning for breast cancer diagnosis from histopathological images: classification and gene expression: review Network Modeling Analysis in Health Informatics and Bioinformatics, 2024 DOI:10.1007/s13721-024-00489-8

[3]	Analysis of Machine Learning Algorithms on Cancer Dataset 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), 2020 DOI:10.1109/ic-ETITE47903.2020.36

[4]	Classification of Breast Lesions using Modified Masood Score and Neural Network Biomedical and Pharmacology Journal, 2018 DOI:10.13005/bpj/1544

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