0.0537). Among all of the 103 targets, 51 (54) got lower GDT-TS (TM-score) lost using linear model. The Pearson’s correlation of linear model (0.4083, 0.4062) is about 8 percent higher than Proq2, but still 10 percent lower than consensus-based method. Among all of the 103 targets, 38 (38) of the targets got a higher Pearson’s correlation than consensus. 4.6.2 Decision Tree Figure 4.6.5 Compare the result of Decision Tree with Proq2 on dataset three Figure 4.6.6 Compare the result of Decision Tree with consensus-based method on dataset three When tested on dataset three, decision tree got a quality lost (0.0640, 0.0635) which is worse than Proq2 (0.0566, 0.0549) and consensus-based method (0.0541, 0.0537). Among all of the 103 targets, only 33 (43) got lower GDT-TS (TM-score) lost when using decision tree. The Pearson’s correlation of decision tree is still much worse than Proq2 and consensus-based method. Among all of the 103 targets, only 20 (20) of the targets got a higher Pearson’s correlation than consensus. 4.6.3 Neural Network
0.0537). Among all of the 103 targets, 51 (54) got lower GDT-TS (TM-score) lost using linear model. The Pearson’s correlation of linear model (0.4083, 0.4062) is about 8 percent higher than Proq2, but still 10 percent lower than consensus-based method. Among all of the 103 targets, 38 (38) of the targets got a higher Pearson’s correlation than consensus. 4.6.2 Decision Tree Figure 4.6.5 Compare the result of Decision Tree with Proq2 on dataset three Figure 4.6.6 Compare the result of Decision Tree with consensus-based method on dataset three When tested on dataset three, decision tree got a quality lost (0.0640, 0.0635) which is worse than Proq2 (0.0566, 0.0549) and consensus-based method (0.0541, 0.0537). Among all of the 103 targets, only 33 (43) got lower GDT-TS (TM-score) lost when using decision tree. The Pearson’s correlation of decision tree is still much worse than Proq2 and consensus-based method. Among all of the 103 targets, only 20 (20) of the targets got a higher Pearson’s correlation than consensus. 4.6.3 Neural Network