last updates before submission
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@ -1,7 +1,7 @@
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import os.path
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import pickle
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from itertools import zip_longest
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from Retrieval.commons import RetrievedSamples, load_sample, DATA_SIZES
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from commons import RetrievedSamples, load_sample, DATA_SIZES
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from os.path import join
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from tqdm import tqdm
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import numpy as np
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@ -57,9 +57,9 @@ for class_name in ['continent']: # 'num_sitelinks_category', 'relative_pageviews
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fig, ax = plt.subplots()
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# train_source = ['train-'+s for s in source]
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train_source = ['$\mathcal{L}_{'+s.replace('FULL', '3.25M').replace('K','\mathrm{K}').replace('M','\mathrm{M}')+'}$' for s in source]
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train_source = ['$L_{'+s.replace('FULL', '3.25M').replace('K','\mathrm{K}').replace('M','\mathrm{M}')+'}$' for s in source]
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# Ms = list(zip(Mtrs, train_source))+list(zip(Mtes, ['test']))
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Ms = list(zip(Mtrs, train_source)) + list(zip(Mtes, ['$\mathcal{U}_{(3.25\mathrm{M})}$']))
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Ms = list(zip(Mtrs, train_source)) + list(zip(Mtes, ['$U_{(3.25\mathrm{M})}$']))
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for M, source in Ms:
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@ -85,7 +85,7 @@ for class_name in ['continent']: # 'num_sitelinks_category', 'relative_pageviews
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# plt.show()
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os.makedirs('plots', exist_ok=True)
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plotpath = f'plots/{class_name}_rel_distrbution.pdf'
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plotpath = f'plots/{class_name}_rel_distrbution_2.pdf'
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print(f'saving plot in {plotpath}')
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plt.savefig(plotpath, bbox_inches='tight')
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@ -87,7 +87,6 @@ def evaluation_report(model: BaseQuantifier,
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Generates a report (a pandas' DataFrame) containing information of the evaluation of the model as according
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to a specific protocol and in terms of one or more evaluation metrics (errors).
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:param model: a quantifier, instance of :class:`quapy.method.base.BaseQuantifier`
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:param protocol: :class:`quapy.protocol.AbstractProtocol`; if this object is also instance of
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:class:`quapy.protocol.OnLabelledCollectionProtocol`, then the aggregation speed-up can be run. This is the protocol
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