def test (indata): prefix='distance_' try: util.set_features(indata, prefix) except NotImplementedError, e: print e return True
def test (indata): try: util.set_features(indata, 'distribution_') _set_distribution(indata) except NotImplementedError, e: print e return True
def test(indata):
try:
util.set_features(indata, 'distribution_')
_set_distribution(indata)
except NotImplementedError, e:
print e
return True
def test (indata): prefix='topfk_' if indata.has_key(prefix+'name'): try: util.set_features(indata, prefix) return _evaluate_top_fisher(indata, prefix) except NotImplementedError, e: print e return True
def test (indata): prefix='classifier_' if indata[prefix+'type']=='kernel': feature_prefix='kernel_' elif indata[prefix+'type']=='knn': feature_prefix='distance_' else: feature_prefix='classifier_' try: util.set_features(indata, feature_prefix) except NotImplementedError, e: print e return True
def test(indata):
try:
util.set_features(indata, 'kernel_')
except NotImplementedError, e:
print e
return True
def test (indata): try: util.set_features(indata, 'kernel_') except NotImplementedError, e: print e return True
# public
########################################################################
def test (indata):
prefix='topfk_'
if indata.has_key(prefix+'name'):
try:
util.set_features(indata, prefix)
return _evaluate_top_fisher(indata, prefix)
except NotImplementedError, e:
print e
return True
prefix='kernel_'
try:
util.set_features(indata, prefix)
names=['Combined', 'AUC', 'Custom']
for name in names:
if indata[prefix+'name']==name:
return eval('_evaluate_'+name.lower()+'(indata, prefix)')
names=['HistogramWordString', 'SalzbergWordString']
for name in names:
if indata[prefix+'name']==name:
return _evaluate_pie(indata, prefix)
# pretty normal kernel
return _evaluate_kernel(indata, prefix)
except NotImplementedError, e:
print e
return True
