Which of the following can act as possible termination conditions in K-Means? 1. For a fixed number of iterations. 2. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum. 3. Centroids do not change between successive iterations. 4. Terminate when RSS falls below a threshold.

The correct answer is: D. 1,2,3,4

All of the options can act as possible termination conditions in K-Means.

1. For a fixed number of iterations: This is a common termination condition, as it is often desirable to have a fixed number of iterations to avoid overfitting.
2. Assignment of observations to clusters does not change between iterations: This is another common termination condition, as it indicates that the clusters have converged.
3. Centroids do not change between successive iterations: This is a less common termination condition, but it can be useful in cases where the clusters are very stable.
4. Terminate when RSS falls below a threshold: This is a more sophisticated termination condition, as it takes into account the quality of the clustering.

In general, it is best to use a combination of termination conditions to ensure that the K-Means algorithm converges to a good solution.