Programming Assignment: K-means Clustering
Machine Learning
Total points: 100
Note: This assignment is for each individual student to complete on his or her
own.
In this assignment, you will implement k-means clustering to achieve image
compression. To get started, you will need to download the starter code and unzip
its contents to the directory where you wish to complete the assignment.
The problem considered in this assignment is to compress the image downloaded
from https://leafyplace.com/types-of-birds/
You are required the complete the following steps:
1. Implement the K-means Clustering algorithm to group pixels into K clusters.
Pixels with similar RGB values fall into the same cluster.
2. Plot a graph to show the change of SSE (sum of squared error). Use SSE to
determine whether the algorithm converges or not.
3. Construct the compressed image.
To get started, open the main script assignmentClustering.m and fill out
the missing code blocks.
What to submit?
A zip file that includes the following items:
1) All codes (70 points)
2) A report that includes (30 points):
a. (20 points) Graph of SSE and compressed images when K = 5, 10,
20
b. (5 points) Explain the impact of K
c. (5 points) Describe how your current implementation can be
potentially improved to achieve better performance.

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