[Solved] Given the code below, what will be the output of labels? import numpy as np from scipy.cluster.vq import kmeans, vq data = np.... Given the code below, what will be the output of labels? | SciPy

SciPy - Clustering and Distance

Given the code below, what will be the output of labels?

import numpy as np
from scipy.cluster.vq import kmeans, vq

data = np.array([[1, 2], [1, 4], [1, 0], [10, 2], [10, 4], [10, 0]])
centroids, _ = kmeans(data, np.array([[1, 2], [10, 2]]))
labels, _ = vq(data, centroids)
print(labels.tolist())

A[0, 0, 0, 1, 1, 1]

B[1, 1, 1, 0, 0, 0]

C[0, 1, 0, 1, 0, 1]

D[1, 0, 1, 0, 1, 0]

Step-by-Step Solution

Solution:

Step 1: Understand data and centroids
Data has two groups: points near (1, y) and points near (10, y). Kmeans with 2 clusters finds centroids near these groups.
Step 2: Assign labels with vq
Points near (1, y) get label 0, points near (10, y) get label 1. So first three points labeled 0, last three labeled 1.
Final Answer:
[0, 0, 0, 1, 1, 1] -> Option A
Quick Check:
Clusters split by x-coordinate: left=0, right=1 [OK]

Quick Trick: Group points by centroid proximity for labels [OK]

Common Mistakes:

Assuming labels are reversed
Mixing up label order
Expecting labels to be random

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More SciPy Quizzes

Given the code below, what will be the output of labels?

Step 1: Understand data and centroids

Step 2: Assign labels with vq

Final Answer:

Quick Check:

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