International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

Cancer classification: A study of eight machine learning algorithms for optimal classification of the nature of cancer

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Abstract

Cancer mainly affects women and is the most dangerous disease in the world. Curing cancer through early detection of cancer and scientific research is our main goal because early detection helps to eliminate cancer completely. After reviewing several articles, we found that there are several techniques available for cancer detection. In this paper, we applied eight data mining techniques: Deep Neural Networks, Artificial Neural Networks, Naive Bayesian Classifier, Classification Trees, Fuzzy C-Means, Logistic Regression, Discriminant Analysis and K-Nearest Neighbor Classifier to this problem and show their significant results on real data. Therefore, among all data mining methods used, good results can be obtained by applying Deep Learning Neural Networks to cancer detection. 

How to Cite This Article

Alaa Khouloud, Atounti Mohamed, Bailoul Charaf Eddine (2022). Cancer classification: A study of eight machine learning algorithms for optimal classification of the nature of cancer . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 3(1), 482-488. DOI: https://doi.org/10.54660/anfo.2022.3.1.23

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