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