def compute_bench(alpha, n_samples, n_features):
lasso_results = []
larslasso_results = []
larslasso_gram_results = []
n_tests = 1000
it = 0
for ns in n_samples:
for nf in n_features:
it += 1
print '=================='
print 'Iteration %s of %s' % (it, max(len(n_samples), len(n_features)))
print '=================='
k = nf // 10
X, Y, X_test, Y_test, coef_ = make_data(
n_samples=ns, n_tests=n_tests, n_features=nf,
noise=0.1, k=k)
X /= np.sqrt(np.sum(X**2, axis=0)) # Normalize data
gc.collect()
print "benching Lasso: "
clf = Lasso(alpha=alpha, fit_intercept=False)
tstart = time()
clf.fit(X, Y)
lasso_results.append(time() - tstart)
gc.collect()
print "benching LassoLARS: "
clf = LassoLARS(alpha=alpha, fit_intercept=False)
tstart = time()
clf.fit(X, Y, normalize=False, precompute=False)
larslasso_results.append(time() - tstart)
gc.collect()
print "benching LassoLARS (precomp. Gram): "
clf = LassoLARS(alpha=alpha, fit_intercept=False)
tstart = time()
clf.fit(X, Y, normalize=False, precompute=True)
larslasso_gram_results.append(time() - tstart)
return lasso_results, larslasso_results, larslasso_gram_results
def compute_bench(alpha, n_samples, n_features):
def LassoFactory(alpha):
return Lasso(alpha=alpha, fit_intercept=False)
def LassoLARSFactory(alpha):
return LassoLARS(alpha=alpha, fit_intercept=False, normalize=False)
lasso_results = []
larslasso_results = []
larslasso_gram_results = []
n_tests = 1000
it = 0
for ns in n_samples:
for nf in n_features:
it += 1
print '=================='
print 'Iteration %s of %s' % (it, max(len(n_samples), len(n_features)))
print '=================='
k = nf // 10
X, Y, X_test, Y_test, coef_ = make_data(
n_samples=ns, n_tests=n_tests, n_features=nf,
noise=0.1, k=k)
X /= np.sqrt(np.sum(X**2, axis=0)) # Normalize data
print "benching Lasso: "
lasso_results.append(bench(LassoFactory(alpha),
X, Y, X_test, Y_test))
print "benching LassoLARS: "
larslasso_results.append(bench(LassoLARSFactory(alpha),
X, Y, X_test, Y_test))
print "benching LassoLARS (precomp. Gram): "
Gram = np.dot(X.T, X)
larslasso_gram_results.append(bench(LassoLARSFactory(alpha),
X, Y, X_test, Y_test, Gram=Gram))
return lasso_results, larslasso_results, larslasso_gram_results
