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sklearn.manifold.locally_linear_embedding 파라미터<Python>/[Sklearn] 2022. 1. 14. 22:37728x90
locally_linear_embedding
sklearn.manifold.locally_linear_embedding(X, *, n_neighbors, n_components, reg=0.001, eigen_solver='auto', tol=1e-06, max_iter=100, method='standard', hessian_tol=0.0001, modified_tol=1e-12, random_state=None, n_jobs=None)
locally_linear_embedding 파라미터
X{array-like, NearestNeighbors}
n_neighborsint
n_componentsint
regfloat, default=1e-3
eigen_solver{‘auto’, ‘arpack’, ‘dense’}, default=’auto’
tolfloat, default=1e-6
max_iterint, default=100
method{‘standard’, ‘hessian’, ‘modified’, ‘ltsa’}, default=’standard’standarduse the standard locally linear embedding algorithm.
hessian_tolfloat, default=1e-4
modified_tolfloat, default=1e-12
random_stateint, RandomState instance, default=None
n_jobsint or None, default=None
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