def test_selects_all():
from sklearn.neighbors import KNeighborsClassifier
from mlxtend.data import wine_data
X, y = wine_data()
knn = KNeighborsClassifier(n_neighbors=4)
sfbs = SFBS(knn, k_features=13, scoring='accuracy', cv=3, print_progress=False)
sfbs.fit(X, y)
assert(len(sfbs.indices_) == 13)
def test_Iris():
from sklearn.neighbors import KNeighborsClassifier
from sklearn.datasets import load_iris
iris = load_iris()
X = iris.data
y = iris.target
knn = KNeighborsClassifier(n_neighbors=4)
sfbs = SFBS(knn, k_features=2, scoring='accuracy', cv=5, print_progress=False)
sfbs.fit(X, y)
assert(sfbs.indices_ == (0, 3))
assert(round(sfbs.k_score_, 2) == 0.96)
