mirror of
https://github.com/clearml/clearml
synced 2025-01-31 17:17:00 +00:00
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
try:
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import joblib
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except ImportError:
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from sklearn.externals 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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import numpy as np
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import matplotlib.pyplot as plt
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from clearml import Task
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# Connecting ClearML with the current process,
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# from here on everything is logged automatically
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task = Task.init(project_name="examples", task_name="scikit-learn joblib example")
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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(solver='liblinear', multi_class='auto') # 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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x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
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y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5
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h = .02 # step size in the mesh
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xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
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plt.figure(1, figsize=(4, 3))
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plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)
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plt.xlabel('Sepal length')
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plt.ylabel('Sepal width')
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plt.xlim(xx.min(), xx.max())
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plt.ylim(yy.min(), yy.max())
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plt.xticks(())
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plt.yticks(())
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plt.show()
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