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37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
import sys
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import time
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from sklearn.model_selection import cross_val_score, StratifiedKFold
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from benchmark import Datasets
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from bayesclass import TAN
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import warnings
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if len(sys.argv) < 2:
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print("Usage: python3 example.py <dataset> [n_folds]")
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exit(1)
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# Warnings are not errors
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warnings.simplefilter("ignore")
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start = time.time()
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random_state = 17
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name = sys.argv[1]
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n_folds = int(sys.argv[2]) if len(sys.argv) == 3 else 5
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dt = Datasets()
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name_list = list(dt) if name == "all" else [name]
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print(f"Accuracy in {n_folds} folds stratified crossvalidation")
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for name in name_list:
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dataset_start = time.time()
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X, y = dt.load(name)
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clf = TAN(random_state=random_state)
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fit_params = dict(
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features=dt.get_features(), class_name=dt.get_class_name(), head=0
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)
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kfold = StratifiedKFold(
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n_splits=n_folds, shuffle=True, random_state=random_state
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)
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score = cross_val_score(clf, X, y, cv=kfold, fit_params=fit_params)
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print(
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f"{name:20s}{'.' * 10}{score.mean():9.7f} "
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f"({time.time()-dataset_start:7.2f} seconds)"
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)
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print(f"Took {time.time()-start:.2f} seconds")
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