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26 lines
634 B
Python
26 lines
634 B
Python
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import joblib
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from sklearn import datasets
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from sklearn.linear_model import LogisticRegression
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from sklearn.model_selection import train_test_split
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from trains import Task
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task = Task.init(project_name="examples", task_name="joblib test")
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iris = datasets.load_iris()
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X = iris.data
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y = iris.target
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
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model = LogisticRegression() # sklearn LogisticRegression class
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model.fit(X_train, y_train)
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joblib.dump(model, 'model.pkl', compress=True)
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loaded_model = joblib.load('model.pkl')
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result = loaded_model.score(X_test, y_test)
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print(result)
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