/usr/bin/svm-easy is in libsvm-tools 3.12-1.1.
This file is owned by root:root, with mode 0o755.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | #! /usr/bin/python
import sys
import os
from subprocess import *
if len(sys.argv) <= 1:
print('Usage: {0} training_file [testing_file]'.format(sys.argv[0]))
raise SystemExit
# svm, grid, and gnuplot executable files
is_win32 = (sys.platform == 'win32')
if not is_win32:
svmscale_exe = "/usr/bin/svm-scale"
svmtrain_exe = "/usr/bin/svm-train"
svmpredict_exe = "/usr/bin/svm-predict"
grid_py = "/usr/bin/svm-grid"
gnuplot_exe = "/usr/bin/gnuplot"
else:
# example for windows
svmscale_exe = r"..\windows\svm-scale.exe"
svmtrain_exe = r"..\windows\svm-train.exe"
svmpredict_exe = r"..\windows\svm-predict.exe"
gnuplot_exe = r"c:\tmp\gnuplot\binary\pgnuplot.exe"
grid_py = r".\grid.py"
assert os.path.exists(svmscale_exe),"svm-scale executable not found"
assert os.path.exists(svmtrain_exe),"svm-train executable not found"
assert os.path.exists(svmpredict_exe),"svm-predict executable not found"
assert os.path.exists(gnuplot_exe),"gnuplot executable not found"
assert os.path.exists(grid_py),"grid.py not found"
train_pathname = sys.argv[1]
assert os.path.exists(train_pathname),"training file not found"
file_name = os.path.split(train_pathname)[1]
scaled_file = file_name + ".scale"
model_file = file_name + ".model"
range_file = file_name + ".range"
if len(sys.argv) > 2:
test_pathname = sys.argv[2]
file_name = os.path.split(test_pathname)[1]
assert os.path.exists(test_pathname),"testing file not found"
scaled_test_file = file_name + ".scale"
predict_test_file = file_name + ".predict"
cmd = '{0} -s "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, train_pathname, scaled_file)
print('Scaling training data...')
Popen(cmd, shell = True, stdout = PIPE).communicate()
cmd = '{0} -svmtrain "{1}" -gnuplot "{2}" "{3}"'.format(grid_py, svmtrain_exe, gnuplot_exe, scaled_file)
print('Cross validation...')
f = Popen(cmd, shell = True, stdout = PIPE).stdout
line = ''
while True:
last_line = line
line = f.readline()
if not line: break
c,g,rate = map(float,last_line.split())
print('Best c={0}, g={1} CV rate={2}'.format(c,g,rate))
cmd = '{0} -c {1} -g {2} "{3}" "{4}"'.format(svmtrain_exe,c,g,scaled_file,model_file)
print('Training...')
Popen(cmd, shell = True, stdout = PIPE).communicate()
print('Output model: {0}'.format(model_file))
if len(sys.argv) > 2:
cmd = '{0} -r "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, test_pathname, scaled_test_file)
print('Scaling testing data...')
Popen(cmd, shell = True, stdout = PIPE).communicate()
cmd = '{0} "{1}" "{2}" "{3}"'.format(svmpredict_exe, scaled_test_file, model_file, predict_test_file)
print('Testing...')
Popen(cmd, shell = True).communicate()
print('Output prediction: {0}'.format(predict_test_file))
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