def question5(filename):
data = 'unifiedCancerData_111.csv'
dist = distortion(
visualize(data, filename, lambda x: hierarchical_clustering(x, 9)),
load_data_table(data))
print('Distortion in question5, hierarchical_clustering = %f (%s)' %
(dist, dist))
def question6(filename):
data = 'unifiedCancerData_111.csv'
dist = distortion(
visualize(data, filename, lambda x: kmeans_clustering(x, 9, 5)),
load_data_table(data))
print('Distortion in question6, kmeans = %f (%s)' % (dist, dist))
def question3(filename):
visualize('unifiedCancerData_3108.csv', filename,
lambda x: kmeans_clustering(x, 15, 5))
def question2(filename):
visualize('unifiedCancerData_3108.csv', filename,
lambda x: hierarchical_clustering(x, 15))
def question6(filename):
data = 'data/unifiedCancerData_111.csv'
dist = distortion(visualize(data, filename,
lambda x: kmeans_clustering(x, 9, 5)),
load_data_table(data))
print('Distortion in question6, kmeans = %f (%s)' % (dist, dist))
def question5(filename):
data = 'data/unifiedCancerData_111.csv'
dist = distortion(visualize(data, filename,
lambda x: hierarchical_clustering(x, 9)),
load_data_table(data))
print('Distortion in question5, hierarchical_clustering = %f (%s)' % (dist, dist))
def question3(filename):
visualize('data/unifiedCancerData_3108.csv', filename,
lambda x: kmeans_clustering(x, 15, 5))
def question2(filename):
visualize('data/unifiedCancerData_3108.csv', filename,
lambda x: hierarchical_clustering(x, 15))