From 8dfb109b410bd8a9da2d8781c2104f5aeb83ef66 Mon Sep 17 00:00:00 2001 From: Alejandro Moreo Date: Thu, 2 May 2024 16:53:44 +0200 Subject: [PATCH] cleaning baselines --- LeQua2024/baselines.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/LeQua2024/baselines.py b/LeQua2024/baselines.py index 73f9246..d35e09a 100644 --- a/LeQua2024/baselines.py +++ b/LeQua2024/baselines.py @@ -12,7 +12,7 @@ from quapy.method.non_aggregative import MaximumLikelihoodPrevalenceEstimation a import quapy.functional as F -# LeQua official baselines +# LeQua official baselines (under development!) # ================================================================================= BINARY_TASKS = ['T1', 'T4'] @@ -40,12 +40,6 @@ def baselines(): yield ACC(new_cls()), "ACC", q_params yield PCC(new_cls()), "PCC", q_params yield PACC(new_cls()), "PACC", q_params - # yield EMQ(CalibratedClassifierCV(new_cls())), "SLD-Platt", wrap_params(wrap_params(lr_params, 'estimator'), 'classifier') - # yield EMQ(new_cls()), "SLD", q_params - # yield EMQ(new_cls()), "SLD-BCTS", {**q_params, 'recalib': ['bcts'], 'val_split': [5]} - # yield MLPE(), "MLPE", None - # if args.task in BINARY_TASKS: - # yield MS2(new_cls()), "MedianSweep2", q_params def main(args): @@ -60,6 +54,9 @@ def main(args): train, gen_val, gen_test = fetch_lequa2024(task=args.task, data_home=args.datadir, merge_T3=True) + # gen_test is None, since the true prevalence vectors for the test samples will be released + # only after the competition ends + print(f'number of classes: {len(train.classes_)}') print(f'number of training documents: {len(train)}') print(f'training prevalence: {F.strprev(train.prevalence())}')