sgkit.variables.sample_pca_explained_variance_spec

sgkit.variables.sample_pca_explained_variance_spec = ArrayLikeSpec(default_name='sample_pca_explained_variance', __doc__='Variance explained by each principal component. These values are equivalent\nto eigenvalues that result from the eigendecomposition of a (N, M) matrix,\ni.e. ``dask_ml.decomposition.TruncatedSVD.explained_variance_``.', kind='f', ndim=1, dims=('components',))

Variance explained by each principal component. These values are equivalent to eigenvalues that result from the eigendecomposition of a (N, M) matrix, i.e. dask_ml.decomposition.TruncatedSVD.explained_variance_.