# ['system_call_20gram_feats'],\
# ['system_call_8gram_feats','system_call_10gram_feats'],\
# ['system_call_5gram_feats', 'system_call_8gram_feats', 'system_call_10gram_feats'],\
# ]
# other dumb feature functions
ff_combos = [['dlls_loaded_feats'],['registry_keys_feats'],['system_call_8gram_feats'],['system_call_8gram_feats','dlls_loaded_feats'],['system_call_8gram_feats','registry_keys_feats']]
for ffs in ff_combos:
value = ffs
print
print "################################################################################"
print "Feature functions: " + str(value)
params['ffs'] = ffs
results = classif.mainTestIter(0, params)
if(isinstance(value, list)):
value = tuple(value)
outputs[value] = results
print "\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%"
import pprint
pp = pprint.PrettyPrinter(indent=4)
print "Results:"
print outputs
print
pp.pprint(outputs)
# ['system_call_8gram_feats','system_call_10gram_feats'],\
# ['system_call_5gram_feats', 'system_call_8gram_feats', 'system_call_10gram_feats'],\
# ]
# other dumb feature functions
ff_combos = [['dlls_loaded_feats'], ['registry_keys_feats'],
['system_call_8gram_feats'],
['system_call_8gram_feats', 'dlls_loaded_feats'],
['system_call_8gram_feats', 'registry_keys_feats']]
for ffs in ff_combos:
value = ffs
print
print "################################################################################"
print "Feature functions: " + str(value)
params['ffs'] = ffs
results = classif.mainTestIter(0, params)
if (isinstance(value, list)):
value = tuple(value)
outputs[value] = results
print "\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%\%"
import pprint
pp = pprint.PrettyPrinter(indent=4)
print "Results:"
print outputs
print
pp.pprint(outputs)
"""params = {'load': None,
'extractFile': 'Output/extractFile',
'extractTestFile': 'Output/extractTestFile',
'splitFile': 'Output/splitFile',
'writePredict': True,
# 'outputFile': 'Output/predict_oneVRest_3grams.csv',
'splitMethod': 0,
'options':{ },
'option':'mode',
'range':['oneVOne','oneVRest','decisionTree']
}"""
params = {'load': 'split',
'extractFile': 'Output/extractFile_2grams',
'extractTestFile': 'Output/extractTestFile',
'splitFile': 'Output/split_bigrams_counts_withhold0',
'writePredict': False,
'outputFile': 'Output/predict_oneVRest_2grams.csv',
'splitMethod': 0,
'options':{
},
'option':'mode',
'range':['logRegress']
}
classif.mainTestIter(0, params)
"""value of splitMethod (used for consistent testing):
0: random
1: last 'withhold' are withheld
2: first 'withhold' are withheld"""
"""params = {'load': None,
'extractFile': 'Output/extractFile',
'extractTestFile': 'Output/extractTestFile',
'splitFile': 'Output/splitFile',
'writePredict': True,
# 'outputFile': 'Output/predict_oneVRest_3grams.csv',
'splitMethod': 0,
'options':{ },
'option':'mode',
'range':['oneVOne','oneVRest','decisionTree']
}"""
params = {
'load': 'split',
'extractFile': 'Output/extractFile_2grams',
'extractTestFile': 'Output/extractTestFile',
'splitFile': 'Output/split_bigrams_counts_withhold0',
'writePredict': False,
'outputFile': 'Output/predict_oneVRest_2grams.csv',
'splitMethod': 0,
'options': {},
'option': 'mode',
'range': ['logRegress']
}
classif.mainTestIter(0, params)
