Quasiconformal Mapping Kernel Machine Learning-Based Intelligent Hyperspectral Data Classification for Internet Information Retrieval

Table 7

Performance comparisons on two databases.

Datasets	Indian Pines dataset		Pavia University dataset
Methods	OA (%)	KC (%)	OA (%)	KC (%)
RBF	73.23	63.73	75.43	68.76
Poly	75.77	66.28	78.08	72.07
Mahal-RBF	76.92	67.79	76.26	69.87
Mahal-Poly	77.64	68.62	79.07	73.24
SK-CV-RBF	67.03	64.23	75.71	69.14
SK-Poly	69.37	66.96	77.62	71.37
NMF-MKL	67.48	64.81	71.57	64.42
KNMF-MKL	68.22	65.63	72.80	65.81
Euclidean-MKL1	74.23	69.63	78.69	72.11
Euclidean-MKL2	76.07	72.84	79.24	72.92
Mahalanobis-MKL1	75.90	73.25	79.78	73.43
Mahalanobis-MKL2	78.22	74.25	79.86	74.16
Proposed Mahalanobis-QMKL1	76.96	74.35	80.27	74.52
Proposed Mahalanobis-QMKL2	79.28	75.85	80.96	75.34