41 lines
946 B
Python
41 lines
946 B
Python
import pandas as pd
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import quapy as qp
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from quapy.method.aggregative import SLD
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from quapy.protocol import APP
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from sklearn.linear_model import LogisticRegression
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import quacc.evaluation as eval
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from quacc.estimator import AccuracyEstimator
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from .data import get_dataset
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qp.environ["SAMPLE_SIZE"] = 100
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pd.set_option("display.float_format", "{:.4f}".format)
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def test_2(dataset_name):
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train, test = get_dataset(dataset_name)
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model = LogisticRegression()
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model.fit(*train.Xy)
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estimator = AccuracyEstimator(model, SLD(LogisticRegression()))
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estimator.fit(train)
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df = eval.evaluation_report(estimator, APP(test, n_prevalences=11, repeats=100))
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# print(df.to_string())
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print(df.to_string())
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def main():
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for dataset_name in [
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# "hp",
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# "imdb",
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"spambase",
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]:
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print(dataset_name)
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test_2(dataset_name)
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print("*" * 50)
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if __name__ == "__main__":
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main()
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