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A hybrid of multiple linear regression clustering model with support vector machine for colorectal cancer tumor size prediction

Shafi, Muhammad Ammar and Rusiman, Mohd Saifullah and Ismail, Shuhaida and Kamardan, Muhamad Ghazali (2019) A hybrid of multiple linear regression clustering model with support vector machine for colorectal cancer tumor size prediction. (IJACSA) International Journal of Advanced Computer Science and Applications, 10 (4). ISSN 21565570

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Abstract

This study proposed the new hybrid model of Multiple Linear Regression Clustering (MLRC) combined with Support Vector Machine (SVM) to predict tumor size of colorectal cancer (CRC). Three models: Multiple Linear Regression (MLR), MLRC and hybrid MLRC with SVM model were compared to get the best model in predicting tumor size of colorectal cancer using two measurement statistical errors. The proposed model of hybrid MLRC with SVM have found two significant clusters whereby, each clusters contained 15 and three significant variables for cluster 1 and 2, respectively. The experiments found that the proposed model tend to be the best model with least value of Mean Square Error (MSE) and Root Mean Square Error (RMSE). This finding has shed light to health practitioner in determining the factors that contribute to colorectal cancer.

Item Type: Article
Uncontrolled Keywords: Colorectal cancer; multiple linear regression; support vector machine; fuzzy c- means; clustering; prediction
Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr Abdul Rahim Mat Radzuan
Date Deposited: 31 Oct 2019 02:40
Last Modified: 31 Oct 2019 02:40
URI: http://eprints.uthm.edu.my/id/eprint/11843
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