A Hybrid of Multiple Linear Regression Clustering Model with Support Vector Machine for Colorectal Cancer Tumor Size Prediction

被引：0

作者：

Shafi, Muhammad Ammar ^{[1
]}

Rusiman, Mohd Saifullah ^{[1
]}

Ismail, Shuhaida ^{[1
]}

Kamardan, Muhamad Ghazali ^{[1
]}

机构：

[1] Univ Tun Hussein Onn Malaysia, Dept Math & Stat, Pagoh Muar 86400, Johor, Malaysia

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2019年 / 10卷 / 04期

关键词：

Colorectal cancer; multiple linear regression; support vector machine; fuzzy c- means; clustering; prediction;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：323 / 328

页数：6

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