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Alejandro Moreo Fernandez 2021-01-25 09:02:11 +01:00
parent 2001c6d852
commit e7527bd7ed
3 changed files with 5 additions and 7 deletions

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@ -16,9 +16,7 @@ import argparse
import torch
import shutil
DEBUG = False
qp.environ['SAMPLE_SIZE'] = settings.SAMPLE_SIZE
def newLR():
return LogisticRegression(max_iter=1000, solver='lbfgs', n_jobs=-1)
@ -118,8 +116,6 @@ def save_results(dataset_name, model_name, optim_loss, *results):
def run(experiment):
qp.environ['SAMPLE_SIZE'] = settings.SAMPLE_SIZE
optim_loss, dataset_name, (model_name, model, hyperparams) = experiment
if is_already_computed(dataset_name, model_name, optim_loss=optim_loss):

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@ -33,6 +33,7 @@ nice = {
'hdy': 'HDy',
'dys': 'DyS',
'epaccmaeptr': 'E(PACC)$_\mathrm{Ptr}$',
'epaccmaemae': 'E(PACC)$_\mathrm{AE}$',
'svmperf':'',
'sanders': 'Sanders',
'semeval13': 'SemEval13',
@ -117,7 +118,7 @@ if __name__ == '__main__':
datasets = qp.datasets.TWITTER_SENTIMENT_DATASETS_TEST
evaluation_measures = [qp.error.ae, qp.error.rae]
gao_seb_methods = ['cc', 'acc', 'pcc', 'pacc', 'sld', 'svmq', 'svmkld', 'svmnkld']
new_methods = ['hdy', 'quanet', 'epaccptr']
new_methods = ['hdy', 'quanet', 'epaccmaeptr', 'epaccmaemae']
gao_seb_ranks, gao_seb_results = get_ranks_from_Gao_Sebastiani()

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@ -367,7 +367,8 @@ class EMQ(AggregativeProbabilisticQuantifier):
s += 1
if not converged:
raise UserWarning('the method has reached the maximum number of iterations; it might have not converged')
#raise UserWarning('the method has reached the maximum number of iterations; it might have not converged')
print('[warning] the method has reached the maximum number of iterations; it might have not converged')
return qs, ps