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

Table 6

L1 Regularization-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	0.2606	0.126	0.1692
LASSO Regression	0.3327	0.3528	0.154	0.1583
Elastic Net Regression	0.3954	0.4147	0.1466	0.1506
Decision Tree	0.9993	0.2416	0.0051	0.1714
Support Vector Regression	0.5382	0.3475	0.1281	0.159
Multilayer Perceptron Regression	0.44	0.0821	0.1411	0.1885
Random Forest Regression	0.8903	0.4844	0.0624	0.1413