diff --git a/examples/linear_model/plot_lar.py b/examples/linear_model/plot_lar.py
deleted file mode 100755
index 1363082a1d382348ecdbbff3053fb5addfc42b87..0000000000000000000000000000000000000000
--- a/examples/linear_model/plot_lar.py
+++ /dev/null
@@ -1,51 +0,0 @@
-#!/usr/bin/env python
-"""
-============================
-Least Angle Regression (LAR)
-============================
-
-Compute LAR path on diabetes dataset.
-
-See: http://en.wikipedia.org/wiki/Least-angle_regression
-
-"""
-print __doc__
-
-# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
-#         Alexandre Gramfort <alexandre.gramfort@inria.fr>
-# License: BSD Style.
-
-from datetime import datetime
-import numpy as np
-import pylab as pl
-
-from scikits.learn import linear_model
-from scikits.learn import datasets
-
-diabetes = datasets.load_diabetes()
-X = diabetes.data
-y = diabetes.target
-
-X[:,6] *= -1 # To reproduce wikipedia LAR page
-
-################################################################################
-# Compute path functions
-
-print "Computing regularization path using the LARS ..."
-start = datetime.now()
-_, _, coefs_ = linear_model.lars_path(X, y, max_features=10, method="lasso")
-print "This took ", datetime.now() - start
-
-###############################################################################
-# Display path
-xx = np.sum(np.abs(coefs_), axis=0)
-xx /= xx[-1]
-pl.plot(xx, coefs_.T)
-ymin, ymax = pl.ylim()
-pl.vlines(xx, ymin, ymax, linestyle='dashed')
-pl.xlabel('|coef| / max|coef|')
-pl.ylabel('Coefficients')
-pl.title('Least Angle Regression (LAR) Path')
-pl.axis('tight')
-pl.show()
-