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Updated documentation for #7947 #8196

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Updated documentation for #7947 #8196

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3 changes: 2 additions & 1 deletion sklearn/decomposition/pca.py
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Expand Up @@ -221,7 +221,8 @@ class PCA(_BasePCA):
The estimated number of components. When n_components is set
to 'mle' or a number between 0 and 1 (with svd_solver == 'full') this
number is estimated from input data. Otherwise it equals the parameter
n_components, or n_features if n_components is None.
n_components, or n_features if n_components is None. For PCA to work
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i know they weren't there before, but I think double backticks around the parameter names and None would be good here?

properly, keep n_samples > n_components.
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this is not specific enough. What do you mean by "properly". eg Will it crash?


noise_variance_ : float
The estimated noise covariance following the Probabilistic PCA model
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