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Table 2 Recognition accuracy by n-fold cross validation procedure for different feature extraction techniques for SVM classification for the TG dataset.

From: Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information

Feature sets

n= 5

n= 6

n= 7

n= 8

n= 9

n= 10

PF1 [23]

38.1

38.4

38.6

38.7

38.8

38.8

PF2 [23]

38.0

38.4

38.5

38.6

38.7

38.8

PF [24]

42.3

42.6

42.7

43.0

43.0

43.1

O [21]

35.8

36.1

36.2

36.1

36.3

36.3

AAC [5]

31.5

31.5

31.7

31.8

31.9

32.0

AAC+HXPZV [5]

35.7

36.0

36.1

36.2

36.3

36.3

ACC [29]

64.9

65.4

65.9

66.2

66.4

66.4

PSSM+PF1 [55]

51.1

51.5

52.0

52.3

52.4

52.7

PSSM+PF2 [55]

50.2

50.4

50.7

50.8

51.0

51.1

PSSM+PF [55]

57.2

57.8

58.0

58.3

58.5

58.8

PSSM+O [55]

46.0

46.3

46.5

46.5

46.7

46.7

PSSM+AAC [55]

43.2

43.5

43.6

43.8

43.8

44.0

PSSM+AAC+HXPZV [55]

45.6

45.9

46.0

46.2

46.3

46.6

Mono-gram [19]

57.2

57.3

58.2

58.4

58.8

58.8

Bi-gram [19]

67.1

67.5

67.6

67.8

68.1

68.1

k -AAP (this paper)

75.9

76.2

76.6

76.7

76.9

77.0