def quantify_OHSUMED():
q=Quantification(method='test', dir_name='QuantOHSUMED') #QuantRCV1 #QuantOHSUMED
[y_train,y_test_list,pred_prob_list,test_files, y_names]=q._read_pickle('texts/cl_prob_'+q.dir_name+'.pickle')
indexes=q._read_pickle('texts/cl_indexes_'+q.dir_name+'.pickle')
td=q._classify_and_count(y_test_list)
#ed=q._expectation_maximization(y_train, pred_prob_list, stop_delta=0.1)
ed=q._exp_max(y_train, pred_prob_list, stop_delta=0.1)
#ed=q._prob_classify_and_count(pred_prob_list)
r=q._count_diff(td, ed)
return r
def quantify_OHSUMED():
q = Quantification(method='test',
dir_name='QuantOHSUMED') #QuantRCV1 #QuantOHSUMED
[y_train, y_test_list, pred_prob_list, test_files,
y_names] = q._read_pickle('texts/cl_prob_' + q.dir_name + '.pickle')
indexes = q._read_pickle('texts/cl_indexes_' + q.dir_name + '.pickle')
td = q._classify_and_count(y_test_list)
#ed=q._expectation_maximization(y_train, pred_prob_list, stop_delta=0.1)
ed = q._exp_max(y_train, pred_prob_list, stop_delta=0.1)
#ed=q._prob_classify_and_count(pred_prob_list)
r = q._count_diff(td, ed)
return r
