def training_for_sigma(sigma):
print "starting debugging:"
from expenv import MultiSplitSet
# select dataset
multi_split_set = MultiSplitSet.get(393)
SPLIT_POINTER = 1
#create mock param object by freezable struct
param = Options()
param.kernel = "WeightedDegreeStringKernel" #"WeightedDegreeRBFKernel" # #
param.wdk_degree = 2
param.cost = 1.0
param.transform = 1.0
param.id = 666
param.base_similarity = sigma
param.degree = 2
param.flags = {}
param.flags["wdk_rbf_on"] = False
param.freeze()
data_train = multi_split_set.get_train_data(SPLIT_POINTER)
data_eval = multi_split_set.get_eval_data(SPLIT_POINTER)
# train
mymethod = Method(param)
mymethod.train(data_train)
print "training done"
assessment = mymethod.evaluate(data_eval)
print assessment
assessment.destroySelf()
return assessment.auROC
def main():
print "starting debugging:"
SPLIT_POINTER = 1
from expenv import MultiSplitSet
from helper import Options
# select dataset
multi_split_set = MultiSplitSet.get(399)
#create mock param object by freezable struct
param = Options()
param.kernel = "WeightedDegreeRBFKernel" #"WeightedDegreeStringKernel"# #
param.wdk_degree = 1
param.cost = 1.0
param.transform = 1.0
param.sigma = 1.0
param.id = 666
param.base_similarity = 1
param.degree = 2
param.freeze()
data_train = multi_split_set.get_train_data(SPLIT_POINTER)
data_eval = multi_split_set.get_eval_data(SPLIT_POINTER)
# train
mymethod = Method(param)
mymethod.train(data_train)
print "training done"
assessment = mymethod.evaluate(data_eval)
print assessment
assessment.destroySelf()
def training_for_sigma(sigma):
print "starting debugging:"
from expenv import MultiSplitSet
# select dataset
multi_split_set = MultiSplitSet.get(393)
SPLIT_POINTER = 1
#create mock param object by freezable struct
param = Options()
param.kernel = "WeightedDegreeStringKernel" #"WeightedDegreeRBFKernel" # #
param.wdk_degree = 2
param.cost = 1.0
param.transform = 1.0
param.id = 666
param.base_similarity = sigma
param.degree = 2
param.flags = {}
param.flags["wdk_rbf_on"] = False
param.freeze()
data_train = multi_split_set.get_train_data(SPLIT_POINTER)
data_eval = multi_split_set.get_eval_data(SPLIT_POINTER)
# train
mymethod = Method(param)
mymethod.train(data_train)
print "training done"
assessment = mymethod.evaluate(data_eval)
print assessment
assessment.destroySelf()
return assessment.auROC
def main():
print "starting debugging:"
SPLIT_POINTER = 1
from expenv import MultiSplitSet
from helper import Options
# select dataset
multi_split_set = MultiSplitSet.get(399)
#create mock param object by freezable struct
param = Options()
param.kernel = "WeightedDegreeRBFKernel" #"WeightedDegreeStringKernel"# #
param.wdk_degree = 1
param.cost = 1.0
param.transform = 1.0
param.sigma = 1.0
param.id = 666
param.base_similarity = 1
param.degree = 2
param.freeze()
data_train = multi_split_set.get_train_data(SPLIT_POINTER)
data_eval = multi_split_set.get_eval_data(SPLIT_POINTER)
# train
mymethod = Method(param)
mymethod.train(data_train)
print "training done"
assessment = mymethod.evaluate(data_eval)
print assessment
assessment.destroySelf()