34 lines
772 B
Python
34 lines
772 B
Python
"""
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======================
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Ordinary Least Squares
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======================
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Simple Ordinary Least Squares example, we draw the linear least
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squares solution for a random set of points in the plane.
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"""
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print __doc__
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import numpy as np
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import pylab as pl
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from sklearn import linear_model
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# this is our test set, it's just a straight line with some
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# gaussian noise
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xmin, xmax = -5, 5
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n_samples = 100
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X = [[i] for i in np.linspace(xmin, xmax, n_samples)]
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Y = 2 + 0.5 * np.linspace(xmin, xmax, n_samples) \
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+ np.random.randn(n_samples, 1).ravel()
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# run the classifier
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clf = linear_model.LinearRegression()
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clf.fit(X, Y)
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# and plot the result
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pl.scatter(X, Y, color='black')
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pl.plot(X, clf.predict(X), color='blue', linewidth=3)
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pl.xticks(())
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pl.yticks(())
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pl.show()
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