43 lines
978 B
Python
43 lines
978 B
Python
#!/usr/bin/env python
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"""
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=====================
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Lasso path using LARS
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=====================
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Computes Lasso Path along the regularization parameter using the LARS
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algorithm on the diabetest dataset.
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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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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 LASSO page
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print "Computing regularization path using the LARS ..."
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_, _, coefs_ = linear_model.lars_path(X, y, method='lasso', verbose=True)
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xx = np.sum(np.abs(coefs_.T), axis=1)
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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('LASSO Path')
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pl.axis('tight')
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pl.show()
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