Parameters for K-means clustering (deprecated, use algorithm_params)
| Name | Type | Description | Notes |
|---|---|---|---|
| n_clusters | int | Number of clusters to form | [optional] [default to 8] |
| max_iter | int | Maximum number of iterations | [optional] [default to 300] |
| random_state | int | Random seed for reproducibility | [optional] [default to 42] |
| n_init | int | Number of times k-means will run with different centroid seeds | [optional] [default to 10] |
| tol | float | Tolerance for convergence | [optional] [default to 1.0E-4] |
| init | str | Method for initialization ('k-means++' or 'random') | [optional] [default to 'k-means++'] |
| verbose | int | Verbosity mode | [optional] [default to 0] |
| copy_x | bool | If True, the original data is not modified | [optional] [default to True] |
| algorithm | str | K-means algorithm to use ('lloyd', 'elkan', or 'auto') | [optional] [default to 'lloyd'] |
from mixpeek.models.kmeans_parameters import KmeansParameters
# TODO update the JSON string below
json = "{}"
# create an instance of KmeansParameters from a JSON string
kmeans_parameters_instance = KmeansParameters.from_json(json)
# print the JSON string representation of the object
print(KmeansParameters.to_json())
# convert the object into a dict
kmeans_parameters_dict = kmeans_parameters_instance.to_dict()
# create an instance of KmeansParameters from a dict
kmeans_parameters_from_dict = KmeansParameters.from_dict(kmeans_parameters_dict)