K-Means Clustering

Model: This model partitions customers into clusters based on survey responses. It assigns each customer to the nearest cluster center by minimizing the squared Euclidean distance, ensuring clusters with low intra-cluster variance and high separation.

$$ \min_{C} \sum_{i=1}^{K} \sum_{x \in C_i} \| x - \mu_i \|^2 $$
$$ \mu_i = \frac{1}{|C_i|} \sum_{x \in C_i} x $$
: 1
: 2
: 3
: 4
: 8
: 7
: 6
: 5
:
: