Improving the Solution of Least Squares Support Vector Machines with Application to a Blast Furnace System

Table 5

Predictive results of LS-SVM model with/without feature and model selection.

Inputs	(𝜎^2,𝐶)	Ascend (99*)	Descend (101)	TSA^†
15	(15, 1)	34/42 = 80.95%	93/158 = 58.86%	127/200 = 63.5%
6	(2^9, 2^8)	73/94 = 77.66%	80/106 = 75.47%	153/200 = 76.5%

99* means 99 observations are ascending trend; TSA^† stands for testing set accuracy.