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Table 7 Absolute improvement (%) wrt the SC baseline when bases are learned from the unlabeled GT data sets

From: High level feature extraction for the self-taught learning algorithm

Training Dictionary size K
Set 100 200 300 500
GT-50
IS-20 −1.67 0.66 4.60 2.54
IS-50 −1.06 −1.00 1.83 −0.86
IS-100 −2.00 −1.67 0.34 −1.40
IS-250 −1.40 −0.60 −0.20 −0.33
GT-100
IS-20 −0.67 0.40 3.40 1.94
IS-50 −2.06 −0.06 1.76 2.74
IS-100 −2.80 −0.14 −0.60 1.14
IS-250 −0.33 0.00 −0.27 0.60
GT-250
IS-20 −0.80 0.20 3.80 3.67
IS-50 −3.06 −0.73 1.56 0.80
IS-100 −2.73 0.00 −0.40 −0.60
IS-250 −2.07 −0.60 0.06 −0.80
GT-500
IS-20 −1.27 0.46 2.73 3.20
IS-50 −1.53 −1.20 0.16 1.60
IS-100 −2.13 −1.07 −0.60 −0.40
IS-250 −0.87 −0.73 −1.34 0.33