Characteristic variables Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates Accurate classification rates
Training set1 Testing set1 Training set2 Testing set1 Training set3 Testing set1 Training set4 Testing set1 Training set5 Testing set5
FEV1, % predicted 0.590 0.783 0.709 0.688 0.599 0.725 0.691 0.775 0.697 0.783
FEV1/FVC, % 0.655 0.826 0.664 0.710 0.682 0.746 0.679 0.797 0.679 0.754
FEV3/FVC, % 0.677 0.806 0.682 0.632 0.751 0.667 0.672 0.729 0.684 0.761
FEF25%, % predicted 0.531 0.768 0.505 0.681 0.525 0.717 0.518 0.775 0.533 0.775
FEF25%/FEV1, % 0.540 0.790 0.522 0.688 0.525 0.725 0.534 0.775 0.598 0.783
FEF50%, % predicted 0.751 0.826 0.760 0.725 0.756 0.783 0.637 0.819 0.760 0.761
FEF50%/FEV1, % 0.720 0.819 0.713 0.717 0.724 0.739 0.717 0.804 0.729 0.768
FEF75%, % predicted 0.690 0.826 0.706 0.667 0.672 0.768 0.681 0.783 0.702 0.775
FEF75%/FEV1, % 0.607 0.826 0.626 0.674 0.621 0.746 0.599 0.783 0.641 0.783
FEF25%-75%, % predicted 0.691 0.819 0.690 0.710 0.697 0.783 0.740 0.819 0.693 0.775
FEF25%-75%/FEV1, % 0.693 0.826 0.695 0.717 0.704 0.746 0.686 0.804 0.713 0.790
R5-R20, kPa·L-1·s# 0.599 0.777 0.607 0.710 0.599 0.752 0.625 0.782 0.648 0.770
X5, kPa·L-1·s# 0.704 0.777 0.652 0.702 0.715 0.752 0.713 0.782 0.704 0.770
Fres, L-1·s# 0.673 0.791 0.668 0.715 0.664 0.771 0.637 0.774 0.657 0.782
FENO, ppb 0.733 0.819 0.769 0.732 0.765 0.746 0.758 0.812 0.744 0.833
Eos in blood, % # 0.663 0.783 0.679 0.688 0.722 0.725 0.726 0.754 0.659 0.768
Eos in blood, cell/ul 0.643 0.761 0.661 0.681 0.715 0.732 0.722 0.717 0.637 0.768
PLT, *10^9/L 0.401 0.790 0.394 0.688 0.383 0.725 0.444 0.775 0.439 0.783