Kernel Negative ε Dragging Linear Regression for Pattern Classification

Table 1

Accuracies (%) of different methods on the GT database.

Number of training samples per class	5	6	7	8	9	10
Our method	70.80	73.53	76.05	80.26	81.33	82.36
DLSR	50.48	50.93	52.80	53.77	53.77	54.56
CLSR	63.58	65.33	67.30	70.57	71.00	71.40
NNLS	68.90	71.02	73.88	76.83	78.27	79.68
-SVM	70.42	72.20	74.93	79.46	80.17	81.92
KNN	59.30	61.76	63.85	67.49	69.23	69.40
SRC	56.18	58.44	60.13	63.09	63.57	64.36
LRC	68.90	71.22	73.78	77.71	79.20	80.68
NDLR	65.66	66.76	69.38	73.60	73.57	74.56