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Table 3 Runtime Performance of svm PRAT on the Disorder Dataset (in seconds).

From: svm PRAT: SVM-based Protein Residue Annotation Toolkit

  w = f = 11 w = f = 13 w = f = 15
  #KER NO YES SP #KER NO YES SP #KER NO YES SP
1.93e+10 83993 45025 1.86 1.92e+10 95098 53377 1.78 1.91e+10 106565 54994 1.93
1.91e+10 79623 36933 2.15 1.88e+10 90715 39237 2.31 1.87e+10 91809 39368 2.33
2.01e+10 99501 56894 1.75 2.05e+10 112863 65035 1.73 2.04e+10 125563 69919 1.75
  1. The runtime performance of svm PRAT was benchmarked for learning a classification model on a 64-bit Intel Xeon CPU 2.33 GHz processor. #KER denotes the number of kernel evaluations for training the SVM model. NO denotes runtime in seconds when the CBLAS library was not used, YES denotes the runtime in seconds when the CBLAS library was used, and SP denotes the speedup achieved using the CBLAS library.
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