def main():
# load sample data
X = multivariate_normal.load_data()
# do repeated bisection clustering
n_clusters = 2
clusters, cluster_centers = repeated_bisection(X, n_clusters)
# show results
show_results(clusters, cluster_centers, n_clusters)
def main():
# load sample data
X = multivariate_normal.load_data()
# do repeated bisection clustering
n_clusters = 2
clusters, cluster_centers = repeated_bisection(X, n_clusters)
# show results
show_results(clusters, cluster_centers, n_clusters)
def main():
# sample data
X = multivariate_normal.load_data()
# kmeans clustering
k = 2
Xnew, new_labels = kmeans(X, k)
# plot
colors = ['r', 'b']
for i in range(k):
plt.scatter(Xnew[new_labels == i, 0],
Xnew[new_labels == i, 1],
color=colors[i], marker='x')
plt.show()
def main():
# sample data
X = multivariate_normal.load_data()
# kmeans++
k = 2
Xnew, new_labels = kmeanspp(X, k)
# plot
colors = ['r', 'b']
for i in range(k):
plt.scatter(Xnew[new_labels == i, 0],
Xnew[new_labels == i, 1],
color=colors[i],
marker='x')
plt.show()
def main():
# sample data
X = multivariate_normal.load_data()
# mean shift clustering
bandwidth = estimate_bandwidth(X, n_samples=500)
cluster_centers, points_labels = mean_shift_clustering(X, bandwidth)
print '*** My mean-shift clustering'
print_results(cluster_centers, points_labels)
# mean shift clustering by sklearn
ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
ms.fit(X)
print '*** Mean-shift clustering by sklearn'
print_results(ms.cluster_centers_, ms.labels_)
# plot results
plot_results(X, cluster_centers, points_labels, ms)
def main():
# sample data
X = multivariate_normal.load_data()
# mean shift clustering
bandwidth = estimate_bandwidth(X, n_samples=500)
cluster_centers, points_labels = mean_shift_clustering(X, bandwidth)
print '*** My mean-shift clustering'
print_results(cluster_centers, points_labels)
# mean shift clustering by sklearn
ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
ms.fit(X)
print '*** Mean-shift clustering by sklearn'
print_results(ms.cluster_centers_, ms.labels_)
# plot results
plot_results(X, cluster_centers, points_labels, ms)
