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Table 1 Cross-validated density prediction accuracy of PNN and CPNN models. Average KL divergence for probabilistic and cascaded probabilistic neural network models predicting continuum 3- and 8-class secondary structure from PSI-BlAST encoded sequence data. Window size and number of hidden nodes are varied. All predictions are for 10-fold cross-validation on the training set (set-174). When standard errors are given in parentheses, the predicted value is the mean of five randomized repeats of cross-validation. in parenthesis.

From: Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures

number of classes

window size

PNN hidden nodes

CPNN hidden nodes

  

0

5

10

15

20

25

30

30

3

11

0.59

0.57

0.53

0.52

0.52

0.52

0.51

 
 

13

0.58

0.57

0.53

0.52

0.51

0.51

0.51

 
 

15

0.58

0.56

0.53

0.52

0.51

0.50

0.49

(0.002)

0.47 (0.002)

 

17

0.58

0.56

0.54

0.52

0.51

0.51

0.51

 
 

19

0.59

0.56

0.54

0.52

0.51

0.52

0.51

 

8

11

0.97

0.97

0.94

0.91

0.92

0.89

0.90

 
 

13

0.97

0.96

0.92

0.90

0.90

0.89

0.89

 
 

15

0.97

0.95

0.92

0.90

0.90

0.89

0.88

(0.001)

0.84 (0.002)

 

17

0.98

0.96

0.93

0.91

0.90

0.89

0.89

 
 

19

0.98

0.97

0.94

0.91

0.92

0.89

0.90