import time
import numpy as np
from sklearn.datasets import fetch_20newsgroups_vectorized
from lightning.classification import CDClassifier
bunch = fetch_20newsgroups_vectorized(subset="all")
X = bunch.data
y = bunch.target
y[y >= 1] = 1
Cs = np.logspace(-3, 3, 20)
for warm_start in (True, False):
clf = CDClassifier(loss="squared_hinge",
tol=1e-3,
max_iter=100,
warm_start=warm_start)
scores = []
start = time.time()
for C in Cs:
clf.C = C
clf.fit(X, y)
scores.append(clf.score(X, y))
print "Total time", time.time() - start
print "Average accuracy", np.mean(scores)
import time
import numpy as np
from sklearn.datasets import fetch_20newsgroups_vectorized
from lightning.classification import CDClassifier
bunch = fetch_20newsgroups_vectorized(subset="all")
X = bunch.data
y = bunch.target
y[y >= 1] = 1
Cs = np.logspace(-3, 3, 20)
for warm_start in (True, False):
clf = CDClassifier(loss="squared_hinge", tol=1e-3, max_iter=100,
warm_start=warm_start)
scores = []
start = time.time()
for C in Cs:
clf.C = C
clf.fit(X, y)
scores.append(clf.score(X, y))
print "Total time", time.time() - start
print "Average accuracy", np.mean(scores)
