Parameters for Spectral clustering algorithm.
| Name | Type | Description | Notes |
|---|---|---|---|
| n_clusters | int | Number of clusters to form | [optional] [default to 8] |
| eigen_solver | str | The eigenvalue decomposition strategy ('arpack', 'lobpcg', 'amg', or None) | [optional] |
| n_components | int | Number of eigenvectors to use for spectral embedding | [optional] |
| 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] |
| gamma | float | Kernel coefficient for rbf, poly, sigmoid, laplacian and chi2 kernels | [optional] [default to 1] |
| affinity | str | How to construct the affinity matrix ('nearest_neighbors', 'rbf', 'precomputed', 'precomputed_nearest_neighbors') | [optional] [default to 'rbf'] |
| n_neighbors | int | Number of neighbors to use when constructing the affinity matrix using nearest neighbors | [optional] [default to 10] |
| eigen_tol | float | Stopping criterion for eigendecomposition | [optional] [default to 0] |
| assign_labels | str | Strategy to assign labels in the embedding space ('kmeans' or 'discretize') | [optional] [default to 'kmeans'] |
| degree | float | Degree of the polynomial kernel. Ignored by other kernels | [optional] [default to 3] |
| coef0 | float | Zero coefficient for polynomial and sigmoid kernels | [optional] [default to 1] |
| kernel_params | Dict[str, object] | Parameters for the kernel function | [optional] |
| n_jobs | int | Number of parallel jobs to run (-1 means using all processors) | [optional] [default to 1] |
| verbose | bool | Verbosity mode | [optional] [default to False] |
from mixpeek.models.spectral_params import SpectralParams
# TODO update the JSON string below
json = "{}"
# create an instance of SpectralParams from a JSON string
spectral_params_instance = SpectralParams.from_json(json)
# print the JSON string representation of the object
print(SpectralParams.to_json())
# convert the object into a dict
spectral_params_dict = spectral_params_instance.to_dict()
# create an instance of SpectralParams from a dict
spectral_params_from_dict = SpectralParams.from_dict(spectral_params_dict)