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Table 5 Absolute improvement (%) wrt the NMF 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

−1.53

0.27

−0.93

−0.54

IS-50

−0.47

1.13

1.20

1.33

IS-100

0.40

−0.07

−0.33

0.33

IS-250

−1.07

0.00

0.20

0.00

GT-100

IS-20

−1.06

−0.2

0.07

−0.80

IS-50

−0.67

1.20

1.67

1.20

IS-100

0.40

−0.40

−0.33

0.46

IS-250

−0.20

−0.33

0.67

0.00

GT-250

IS-20

−2.53

−0.26

0.47

−0.34

IS-50

−0.93

1.60

1.67

1.13

IS-100

−0.06

0.27

0.47

−0.80

IS-250

−0.27

0.00

0.07

0.00

GT-500

IS-20

−3.06

−0.93

0.27

−0.94

IS-50

−1.67

1.87

1.33

1.06

IS-100

−0.40

−0.33

−0.13

−0.74

IS-250

−0.87

−0.40

−0.67

0.00