forked from moreo/QuaPy
import fix
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import quapy as qp
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import quapy as qp
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from data import LabelledCollection
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from quapy.data import LabelledCollection
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from method.base import BaseQuantifier, BinaryQuantifier
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from quapy.method.base import BinaryQuantifier
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from model_selection import GridSearchQ
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from quapy.model_selection import GridSearchQ
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from quapy.method.aggregative import PACC, AggregativeProbabilisticQuantifier
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from quapy.method.aggregative import AggregativeProbabilisticQuantifier
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from quapy.protocol import APP
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from quapy.protocol import APP
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import numpy as np
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import numpy as np
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from sklearn.linear_model import LogisticRegression
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from sklearn.linear_model import LogisticRegression
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@ -1,12 +1,11 @@
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import numpy as np
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import numpy as np
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from sklearn.calibration import CalibratedClassifierCV
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from sklearn.linear_model import LogisticRegression
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from sklearn.linear_model import LogisticRegression
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import quapy as qp
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import quapy as qp
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import quapy.functional as F
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import quapy.functional as F
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from data.datasets import LEQUA2022_SAMPLE_SIZE, fetch_lequa2022
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from quapy.data.datasets import LEQUA2022_SAMPLE_SIZE, fetch_lequa2022
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from evaluation import evaluation_report
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from quapy.evaluation import evaluation_report
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from method.aggregative import EMQ
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from quapy.method.aggregative import EMQ
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from model_selection import GridSearchQ
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from quapy.model_selection import GridSearchQ
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import pandas as pd
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import pandas as pd
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"""
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"""
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@ -2,16 +2,14 @@ from abc import abstractmethod
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from copy import deepcopy
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from copy import deepcopy
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from typing import Callable, Union
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from typing import Callable, Union
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import numpy as np
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import numpy as np
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from joblib import Parallel, delayed
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from scipy import optimize
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from scipy import optimize
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from sklearn.base import BaseEstimator, clone
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from sklearn.base import BaseEstimator
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from sklearn.calibration import CalibratedClassifierCV
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from sklearn.calibration import CalibratedClassifierCV
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from sklearn.metrics import confusion_matrix
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from sklearn.metrics import confusion_matrix
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from sklearn.model_selection import StratifiedKFold, cross_val_predict
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from sklearn.model_selection import cross_val_predict
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from tqdm import tqdm
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import quapy as qp
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import quapy as qp
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import quapy.functional as F
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import quapy.functional as F
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from classification.calibration import NBVSCalibration, BCTSCalibration, TSCalibration, VSCalibration
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from quapy.classification.calibration import NBVSCalibration, BCTSCalibration, TSCalibration, VSCalibration
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from quapy.classification.svmperf import SVMperf
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from quapy.classification.svmperf import SVMperf
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from quapy.data import LabelledCollection
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from quapy.data import LabelledCollection
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from quapy.method.base import BaseQuantifier, BinaryQuantifier, OneVsAllGeneric
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from quapy.method.base import BaseQuantifier, BinaryQuantifier, OneVsAllGeneric
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@ -7,7 +7,6 @@ from sklearn.model_selection import GridSearchCV, cross_val_predict
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from tqdm import tqdm
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from tqdm import tqdm
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import quapy as qp
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import quapy as qp
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from evaluation import evaluate_on_samples
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from quapy import functional as F
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from quapy import functional as F
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from quapy.data import LabelledCollection
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from quapy.data import LabelledCollection
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from quapy.model_selection import GridSearchQ
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from quapy.model_selection import GridSearchQ
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@ -178,7 +177,7 @@ class Ensemble(BaseQuantifier):
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For each model in the ensemble, the performance is measured in terms of _error_name_ on the quantification of
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For each model in the ensemble, the performance is measured in terms of _error_name_ on the quantification of
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the samples used for training the rest of the models in the ensemble.
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the samples used for training the rest of the models in the ensemble.
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"""
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"""
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from quapy.evaluation import evaluate
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from quapy.evaluation import evaluate_on_samples
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error = qp.error.from_name(error_name)
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error = qp.error.from_name(error_name)
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tests = [m[3] for m in self.ensemble]
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tests = [m[3] for m in self.ensemble]
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scores = []
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scores = []
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@ -6,7 +6,7 @@ import torch
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from torch.nn import MSELoss
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from torch.nn import MSELoss
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from torch.nn.functional import relu
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from torch.nn.functional import relu
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from protocol import UPP
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from quapy.protocol import UPP
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from quapy.method.aggregative import *
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from quapy.method.aggregative import *
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from quapy.util import EarlyStop
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from quapy.util import EarlyStop
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6
setup.py
6
setup.py
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@ -14,6 +14,7 @@ def get_version(rel_path):
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return line.split(delim)[1]
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return line.split(delim)[1]
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else:
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else:
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raise RuntimeError("Unable to find version string.")
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raise RuntimeError("Unable to find version string.")
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# Arguments marked as "Required" below must be included for upload to PyPI.
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# Arguments marked as "Required" below must be included for upload to PyPI.
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# Fields marked as "Optional" may be commented out.
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# Fields marked as "Optional" may be commented out.
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@ -114,7 +115,7 @@ setup(
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python_requires='>=3.6, <4',
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python_requires='>=3.6, <4',
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install_requires=['scikit-learn', 'pandas', 'tqdm', 'matplotlib'],
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install_requires=['scikit-learn', 'pandas', 'tqdm', 'matplotlib', 'joblib', 'xlrd', 'abstention'],
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# List additional groups of dependencies here (e.g. development
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# List additional groups of dependencies here (e.g. development
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# dependencies). Users will be able to install these using the "extras"
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# dependencies). Users will be able to install these using the "extras"
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project_urls={ # Optional
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project_urls={ # Optional
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'Contributors': 'https://github.com/HLT-ISTI/QuaPy/graphs/contributors',
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'Contributors': 'https://github.com/HLT-ISTI/QuaPy/graphs/contributors',
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'Bug Reports': 'https://github.com/HLT-ISTI/QuaPy/issues',
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'Bug Reports': 'https://github.com/HLT-ISTI/QuaPy/issues',
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'Documentation': 'https://github.com/HLT-ISTI/QuaPy/wiki',
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'Wiki': 'https://github.com/HLT-ISTI/QuaPy/wiki',
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'Documentation': 'https://hlt-isti.github.io/QuaPy/build/html/index.html',
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'Source': 'https://github.com/HLT-ISTI/QuaPy/',
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'Source': 'https://github.com/HLT-ISTI/QuaPy/',
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},
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},
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)
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)
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