25 lines
827 B
Python
25 lines
827 B
Python
import quapy as qp
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from sklearn.linear_model import LogisticRegression
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from quapy.evaluation import evaluation_report
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def newLR():
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return LogisticRegression(n_jobs=-1)
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quantifiers = {'CC':qp.method.aggregative.CC(newLR()),
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'ACC':qp.method.aggregative.ACC(newLR()),
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'PCC':qp.method.aggregative.PCC(newLR()),
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'PACC':qp.method.aggregative.PACC(newLR()),
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'HDy':qp.method.aggregative.DistributionMatching(newLR()),
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'EMQ':qp.method.aggregative.EMQ(newLR())}
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for quant_name, quantifier in quantifiers.items():
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print("Experiment with "+quant_name)
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train, test_gen = qp.datasets.fetch_IFCB()
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quantifier.fit(train)
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report = evaluation_report(quantifier, protocol=test_gen, error_metrics=['mae'], verbose=True)
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print(report.mean())
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