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Some Improvements and comments #30

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7954ee9
Some Improvements and comments
aditi15053 Oct 16, 2023
55491f2
Some improvement and comments
aditi15053 Oct 16, 2023
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42 changes: 19 additions & 23 deletions k_means_clustering/model.py
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Original file line number Diff line number Diff line change
@@ -1,42 +1,38 @@
import random

from k_means_clustering.data import inputs
from k_means_clustering.utils import KMeans, bottom_up_cluster, \
generate_clusters, get_values
from k_means_clustering.utils import KMeans, bottom_up_cluster, generate_clusters, get_values

if __name__ == '__main__':
# Set the random seed for reproducibility
random.seed(0)
cluster = KMeans(3)
cluster.train(inputs=inputs)

# Perform k-means clustering with k=3
kmeans_3 = KMeans(3)
kmeans_3.train(inputs=inputs)
print("3-means:")
print(cluster.means)
print(kmeans_3.means)
print()

random.seed(0)
cluster = KMeans(2)
cluster.train(inputs=inputs)
# Perform k-means clustering with k=2
kmeans_2 = KMeans(2)
kmeans_2.train(inputs=inputs)
print("2-means:")
print(cluster.means)
print(kmeans_2.means)
print()

# for k in range(1, len(inputs) + 1):
# print(k, squared_clustering_errors(inputs, k))
# print()

# recolor_image('/home/amogh/Pictures/symantec.png')

print("bottom up hierarchical clustering")

# Perform hierarchical clustering
print("Bottom-up hierarchical clustering")
base_cluster = bottom_up_cluster(inputs)
print(base_cluster)

print()
print("three clusters, min:")
# Generate three clusters with the minimum size
print("Three clusters, min:")
for cluster in generate_clusters(base_cluster, 3):
print(get_values(cluster))

print()
print("three clusters, max:")
# Generate three clusters with the maximum size
print("Three clusters, max:")
base_cluster = bottom_up_cluster(inputs, max)
for cluster in generate_clusters(base_cluster, 3):
print(get_values(cluster))
print(get_values(cluster))