View source: R/auto_generated_wrappers.R
Principal Component Analysis (PCA)
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n_components |
Desired dimensionality of output data |
copy |
If FALSE, data passed to fit are overwritten and running fit(X).transform(X) will not yield the expected results, use fit_transform(X) instead. |
whiten |
When TRUE (FALSE by default) the |
svd_solver |
'auto' is selected by a default policy based on |
tol |
Tolerance for singular values computed by svd_solver == 'arpack'. |
iterated_power |
Number of iterations for the power method computed by svd_solver == 'randomized'. |
random_state |
If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If NULL, the random number generator is the RandomState instance used by |
verbose |
Verbose or not |
backend |
Which backend to use. Options are 'auto', 'sklearn', 'h2o4gpu'. Saves as attribute for actual backend used. |
gpu_id |
ID of the GPU on which the algorithm should run. Only used by h2o4gpu backend. |
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