52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
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#!/usr/bin/env python
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"""
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============================
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Least Angle Regression (LAR)
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============================
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Compute LAR path on diabetes dataset.
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See: http://en.wikipedia.org/wiki/Least-angle_regression
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"""
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print __doc__
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# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
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# Alexandre Gramfort <alexandre.gramfort@inria.fr>
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# License: BSD Style.
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from datetime import datetime
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import numpy as np
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import pylab as pl
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from scikits.learn import linear_model
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from scikits.learn import datasets
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diabetes = datasets.load_diabetes()
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X = diabetes.data
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y = diabetes.target
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X[:,6] *= -1 # To reproduce wikipedia LAR page
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################################################################################
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# Compute path functions
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print "Computing regularization path using the LARS ..."
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start = datetime.now()
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_, _, coefs_ = linear_model.lars_path(X, y, max_features=10, method="lasso")
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print "This took ", datetime.now() - start
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###############################################################################
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# Display path
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xx = np.sum(np.abs(coefs_), axis=0)
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xx /= xx[-1]
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pl.plot(xx, coefs_.T)
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ymin, ymax = pl.ylim()
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pl.vlines(xx, ymin, ymax, linestyle='dashed')
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pl.xlabel('|coef| / max|coef|')
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pl.ylabel('Coefficients')
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pl.title('Least Angle Regression (LAR) Path')
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pl.axis('tight')
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pl.show()
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