Kmeans

Python module: cuvs.cluster.mg.kmeans

fit

@auto_sync_multi_gpu_resources

1 def fit( KMeansParams params, X, centroids=None, sample_weights=None, resources=None )

Find clusters with single-node multi-GPU k-means using host data.

Parameters

Name	Type	Description
`params`	`KMeansParams`	Parameters to use to fit KMeans model.
`X`	`host array-like`	Training instances, shape (m, k). Must be C-contiguous float32 or float64 host data.
`centroids`	`host array-like, optional`	Initial centroids when `params.init_method == "Array"` and output centroids for all init methods. If omitted, a host NumPy output array is allocated unless `init_method == "Array"`.
`sample_weights`	`host array-like, optional`	Optional weights per observation. Must be C-contiguous and have the same dtype as X.
`resources`	`cuvs.common.Resources, optional`

Returns

FitOutput centroids is a host NumPy array containing the computed centroids, inertia is the final objective value, and n_iter is the number of iterations run.