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adding all svm-perf-based quantifiers with timeout

This commit is contained in:
Alejandro Moreo Fernandez 2021-01-15 18:54:03 +01:00
parent d510630d3b
commit d197167cfd
2 changed files with 7 additions and 8 deletions
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13
TweetSentQuant/experiments.py
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@ -12,6 +12,7 @@ import argparse
parser = argparse.ArgumentParser(description='Run experiments for Tweeter Sentiment Quantification')
parser.add_argument('results', metavar='RESULT_PATH', type=str, help='path to the directory where to store the results')
parser.add_argument('svmperfpath', metavar='SVMPERF_PATH', type=str, help='path to the directory with svmperf')
args = parser.parse_args()
@ -26,11 +27,11 @@ def quantification_models():
yield 'pcc', qp.method.aggregative.PCC(newLR()), lr_params
yield 'pacc', qp.method.aggregative.PACC(newLR()), lr_params
yield 'sld', qp.method.aggregative.EMQ(newLR()), lr_params
#yield 'svmq', OneVsAll(qp.method.aggregative.SVMQ(settings.SVMPERF_HOME)), svmperf_params
#yield 'svmkld', OneVsAll(qp.method.aggregative.SVMKLD(settings.SVMPERF_HOME)), svmperf_params
#yield 'svmnkld', OneVsAll(qp.method.aggregative.SVMNKLD(settings.SVMPERF_HOME)), svmperf_params
yield 'svmmae', OneVsAll(qp.method.aggregative.SVMAE(settings.SVMPERF_HOME)), svmperf_params
yield 'svmmrae', OneVsAll(qp.method.aggregative.SVMRAE(settings.SVMPERF_HOME)), svmperf_params
yield 'svmq', OneVsAll(qp.method.aggregative.SVMQ(args.svmperfpath)), svmperf_params
yield 'svmkld', OneVsAll(qp.method.aggregative.SVMKLD(args.svmperfpath)), svmperf_params
yield 'svmnkld', OneVsAll(qp.method.aggregative.SVMNKLD(args.svmperfpath)), svmperf_params
yield 'svmmae', OneVsAll(qp.method.aggregative.SVMAE(args.svmperfpath)), svmperf_params
yield 'svmmrae', OneVsAll(qp.method.aggregative.SVMRAE(args.svmperfpath)), svmperf_params
# 'mlpe': lambda learner: MaximumLikelihoodPrevalenceEstimation(),
@ -85,7 +86,7 @@ def run(experiment):
return
else:
print(f'running dataset={dataset_name} model={model_name} loss={optim_loss}')
benchmark_devel = qp.datasets.fetch_twitter(dataset_name, for_model_selection=True, min_df=5, pickle=True)
benchmark_devel.stats()

2
TweetSentQuant/settings.py
View File

@ -1,5 +1,3 @@
import multiprocessing
N_JOBS = -2 #multiprocessing.cpu_count()
SVMPERF_HOME = '../svm_perf_quantification'