What are the key parameters for clustering in TensorFlow?

What are the key parameters for clustering in TensorFlow?

In TensorFlow, key parameters for clustering include the number of clusters, distance metric, and initialization method.

Can you explain how to choose the number of clusters?

Choosing the number of clusters can be done using methods like the Elbow method or Silhouette score to evaluate clustering quality.

What distance metrics are commonly used?

Common distance metrics include Euclidean, Manhattan, and Cosine similarity, depending on the data characteristics.

How does initialization affect clustering results?

Initialization can significantly impact clustering results; methods like K-means++ help in selecting better initial centroids.