A New Rule-Based Classification Method Using Shape-Based Properties of Spectral Curves

Table 4

Classification results for real waste dataset.

Metrics	Rule-based method	SVM (a)	SVM (b)	SVM (c)	SVM (d)	SVM (e)
Overall accuracy	0.9842	0.9770	0.9826	0.9805	0.9760	0.9586
Precision	0.9842	0.9398	0.9698	0.9807	0.9856	0.9854
Sensitivity	0.9498	0.9477	0.9434	0.9353	0.9208	0.8831
False positive Rate	0.0075	0.0093	0.0098	0.0119	0.0152	0.0267
F1-score	0.9661	0.9396	0.9540	0.9556	0.9504	0.9290
Kappa	0.9506	0.9283	0.9456	0.9392	0.9249	0.8707

(a) Solver: C-SVC; classification type: one-versus-all; kernel: RBF; C-value: 0.2; threshold: 0.2. (b) Solver: C-SVC; classification type: one-versus-all; kernel: RBF; C-value: 0.2; threshold: 0.3. (c) Solver: C-SVC; classification type: one-versus-all; kernel: RBF; C-value: 0.2; threshold: 0.4. (d) Solver: C-SVC; classification type: one-versus-all; kernel: RBF; C-value: 0.2; threshold: 0.5. (e) Solver: C-SVC; classification type: one-versus-all; kernel: RBF; C-value: 0.2; threshold: 0.6.