def test_covtype_memorize():
with timer("Cuda treelearn"):
forest = RandomForestClassifier(bootstrap = False)
forest.fit(x, y, bfs_threshold = 500000)
with timer("Predict"):
diff, total = util.test_diff(forest.predict(x), y)
print "%s(Wrong)/%s(Total). The error rate is %f." % (diff, total, diff/float(total))
assert diff == 0, "Didn't perfectly memorize, got %d wrong" % diff
def test_digits_memorize():
with timer("Cuda treelearn"):
forest = RandomForestClassifier(n_estimators = n_estimators/2, bootstrap = False)
forest.fit(x, y)
with timer("Predict"):
diff, total = util.test_diff(forest.predict(x), y)
print "%s (Wrong) / %s (Total). The error rate is %f." % (diff, total, diff/float(total))
assert diff == 0, "Didn't memorize, got %d wrong" % diff
def test_covtype_memorize():
with timer("Cuda treelearn"):
forest = RandomForestClassifier(bootstrap = False)
forest.fit(x, y, bfs_threshold = 500000)
with timer("Predict"):
diff, total = util.test_diff(forest.predict(x), y)
print("%s(Wrong)/%s(Total). The error rate is %f." % (diff, total, diff/float(total)))
assert diff == 0, "Didn't perfectly memorize, got %d wrong" % diff