def answer_q10():
"""
generates clusters, figure out distoration and return x & y values
"""
data_sources = [viz.DATA_111_URL, viz.DATA_290_URL, viz.DATA_896_URL]
x_vals = range(6, 21)
y_vals_hier = {}
y_vals_kmean = {}
for idx in range(len(data_sources)):
# 0. Generate data_field & cluster_list
clust_list, data_table = closest_pair.create_cluster_list(
data_sources[idx])
y_vals_hier[idx] = []
# 1. calculate values for hierarchical - decreasing order
for clust_size in reversed(x_vals):
clust_list = closest_pair.hierarchical_clustering(clust_list,
clust_size)
clust_error = closest_pair.compute_distortions(clust_list,
data_table)
y_vals_hier[idx].insert(0, clust_error)
# 2. calculate values for kmeans - decreasing order
y_vals_kmean[idx] = []
for clust_size in x_vals:
clust_list, data_table = closest_pair.create_cluster_list(
data_sources[idx])
clust_list = closest_pair.kmeans_clustering(clust_list,
clust_size, 5)
clust_error = closest_pair.compute_distortions(clust_list,
data_table)
y_vals_kmean[idx].append(clust_error)
return x_vals, y_vals_hier, y_vals_kmean
def test_q7():
clust_list, data_table = create_cluster_list(URL)
print(closest_pair.compute_distortions(clust_list, data_table))
test1 = closest_pair.hierarchical_clustering(clust_list, 16)
print(closest_pair.compute_distortions(test1, data_table))
clust_list, data_table = create_cluster_list(URL)
test2 = closest_pair.kmeans_clustering(clust_list, 16, 5)
print(closest_pair.compute_distortions(test2, data_table))
""" code to answer question 7 """ import closest_pair import alg_project3_viz URL = alg_project3_viz.DATA_111_URL clust_list, data_table = closest_pair.create_cluster_list(URL) test1 = closest_pair.hierarchical_clustering(clust_list,9) print(closest_pair.compute_distortions(test1, data_table)) clust_list, data_table = closest_pair.create_cluster_list(URL) test2 = closest_pair.kmeans_clustering(clust_list,9,5) print(closest_pair.compute_distortions(test2, data_table))