What is the definition of the verbose parameter in scikit learn kmeans clustering

Question

Here is the kmeans algorithm class from scikit learn.

class sklearn.cluster.KMeans(n_clusters=8, init='k-means++', n_init=10, max_iter=300, tol=0.0001, precompute_distances=True, verbose=0, random_state=None, copy_x=True, n_jobs=1)¶ 

An interest in knowing what “verbose” means, and on output it shows the values ​​of inertia, also not sure what that means. They are not explained in the documentation. Any help would be greatly appreciated.

Answer 1

Verbose means that it displays messages that can be useful for debugging and for understanding how this is done.

Inertia is the sum of the squared distance for each point to the nearest centroid, i.e. to the assigned cluster. You can find more information about this here .