def gaussian_3():
gaussian3 = load_3gaussian()
plot(em(gaussian3, 3, 70), gaussian3)
def gaussian_3():
gaussian3 = load_3gaussian()
plot(em(gaussian3, 3, 70), gaussian3)
__author__ = 'jiachiliu'
from nulearn.dataset import load_2gaussian, load_3gaussian
from nulearn.clustering import KMeans
import matplotlib.pyplot as plt
def plot(clusters):
colors = ['r', 'g', 'b']
for k in clusters:
split = clusters[k]
plt.scatter(split[:, 0], split[:, 1], marker='o', c=colors[k])
plt.show()
if __name__ == '__main__':
data = load_3gaussian()
cf = KMeans()
K = 3
cf.fit(data, K=K, max_iter=20)
for k in range(K):
print 'n%s = %s' % (k, len(cf.clusters[k]))
plot(cf.clusters)