Improving K-Means

K-Means is a simple yet often flawed algorithm that can easily converge to suboptimal solutions, resulting in high quantization error. The challenge lies in finding better algorithms that yield more consistent and closer-to-optimal results. Bad outcomes can be identified by significant variations in error values, indicating that the algorithm is not performing as effectively as it could.