Systematic Framework to Predict Early-Stage Liver Carcinoma Using Hybrid of Feature Selection Techniques and Regression Techniques

Table 10

Quasi-Constant Elimination-based Regression algorithms with accuracy and error rate during training and testing.

Models	Accuracy (R2-Score) training (↑)	Accuracy (R2-Score) testing (↑)	MSE training (↓)	MSE testing (↓)
Linear Regression	0.5534	0.2594	0.126	0.1694
Ridge Regression	0.5534	0.2612	0.126	0.1692
LASSO Regression	0.3511	0.3364	0.1518	0.1603
Elastic Net Regression	0.4078	0.4019	0.1451	0.1522
Decision Tree	0.9993	0.0318	0.0051	0.1936
Support Vector Regression	0.7063	0.1806	0.1022	0.1782
Multilayer Perceptron Regression	−33.3501	−24.4743	1.1048	0.9933
Random Forest Regression	0.8912	0.4864	0.0622	0.141