From e95bc43c7001b3b287daefe371db4ba6248bd590 Mon Sep 17 00:00:00 2001
From: Fabian Pedregosa <fabian.pedregosa@inria.fr>
Date: Wed, 16 Jun 2010 15:55:59 +0200
Subject: [PATCH] Add the diabetes dataset and modify the LAR example.
---
examples/glm/plot_lar.py | 20 +-
.../plot_lasso_coordinate_descent_path.py | 8 +-
scikits/learn/datasets/data/diabetes.csv | 442 ++++++++++++++++++
scikits/learn/glm.py | 7 +-
scikits/learn/src/minilearn/minilearn.c | 2 +-
5 files changed, 465 insertions(+), 14 deletions(-)
create mode 100644 scikits/learn/datasets/data/diabetes.csv
diff --git a/examples/glm/plot_lar.py b/examples/glm/plot_lar.py
index 2bbd9a7786..75eba0a3c5 100644
--- a/examples/glm/plot_lar.py
+++ b/examples/glm/plot_lar.py
@@ -15,17 +15,17 @@ import pylab as pl
from scikits.learn import glm
-n_samples, n_features = 50, 10
+n_samples, n_features = 500, 10
np.random.seed(0)
-y = np.random.randn(n_samples)
+Y = np.random.randn(n_samples)
X = np.random.randn(n_samples, n_features)
from scikits.learn import datasets
-# diabetes = datasets.load_diabetes()
-# X = diabetes.data
-# Y = diabetes.target
+diabetes = datasets.load_diabetes()
+X = diabetes.data
+Y = diabetes.target
################################################################################
# Fit models
@@ -39,18 +39,18 @@ eps = 1e-2 # the smaller it is the longer is the path
print "Computing regularization path using the LARS ..."
start = datetime.now()
-clf = glm.LeastAngleRegression().fit(X, y, n_features=7)
+clf = glm.LeastAngleRegression().fit(X, Y, n_features=9, normalize=False)
print "This took ", datetime.now() - start
-alphas = -np.log10(np.abs(clf.alphas_))
+alphas = -np.log10(clf.alphas_)
-# Display results
-color_iter = cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
+# # Display results
+color_iter = cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k' , 'b', 'c', 'c'])
for coef_, color in zip(clf.coef_, color_iter):
pl.plot(alphas, coef_.T, color)
-
+pl.vlines(alphas, -200, 550)
pl.xlabel('-Log(lambda)')
pl.ylabel('weights')
pl.title('Least Angle Regression (LAR) Paths')
diff --git a/examples/plot_lasso_coordinate_descent_path.py b/examples/plot_lasso_coordinate_descent_path.py
index d20d9e2767..28b136d115 100644
--- a/examples/plot_lasso_coordinate_descent_path.py
+++ b/examples/plot_lasso_coordinate_descent_path.py
@@ -17,12 +17,18 @@ import pylab as pl
from scikits.learn.glm import lasso_path, enet_path
-n_samples, n_features, maxit = 5, 10, 30
+n_samples, n_features, maxit = 442, 10, 50
+
+from scikits.learn import datasets
np.random.seed(0)
y = np.random.randn(n_samples)
X = np.random.randn(n_samples, n_features)
+data = datasets.load_diabetes()
+X = data.data
+y = data.target
+
################################################################################
# Fit models
################################################################################
diff --git a/scikits/learn/datasets/data/diabetes.csv b/scikits/learn/datasets/data/diabetes.csv
new file mode 100644
index 0000000000..fa914a30a9
--- /dev/null
+++ b/scikits/learn/datasets/data/diabetes.csv
@@ -0,0 +1,442 @@
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diff --git a/scikits/learn/glm.py b/scikits/learn/glm.py
index f333921b1a..51e6659b55 100644
--- a/scikits/learn/glm.py
+++ b/scikits/learn/glm.py
@@ -908,9 +908,12 @@ class LeastAngleRegression (object):
n_features : number of features to enter the model
"""
- X = np.asanyarray(X, dtype=np.float64, order='C')
- Y = np.asanyarray(Y, dtype=np.float64, order='C')
+ X = np.ascontiguousarray (X, dtype=np.float64)
+ Y = np.ascontiguousarray (Y, dtype=np.float64)
+ assert X.shape[0] == Y.shape[0], ValueError (
+ "Shape mismatch in input array")
+
from . import minilearn
if n_features is None:
diff --git a/scikits/learn/src/minilearn/minilearn.c b/scikits/learn/src/minilearn/minilearn.c
index 70953412a6..8067633a0c 100644
--- a/scikits/learn/src/minilearn/minilearn.c
+++ b/scikits/learn/src/minilearn/minilearn.c
@@ -1,4 +1,4 @@
-/* Generated by Cython 0.11.2 on Tue Jun 15 14:58:10 2010 */
+/* Generated by Cython 0.11.2 on Wed Jun 16 11:04:22 2010 */
#define PY_SSIZE_T_CLEAN
#include "Python.h"
--
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