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Diffstat (limited to 'docs/ml-features.md')
| -rw-r--r-- | docs/ml-features.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/ml-features.md b/docs/ml-features.md index e41bf78521..746593fb9e 100644 --- a/docs/ml-features.md +++ b/docs/ml-features.md @@ -768,7 +768,7 @@ for more details on the API. `StandardScaler` transforms a dataset of `Vector` rows, normalizing each feature to have unit standard deviation and/or zero mean. It takes parameters: * `withStd`: True by default. Scales the data to unit standard deviation. -* `withMean`: False by default. Centers the data with mean before scaling. It will build a dense output, so this does not work on sparse input and will raise an exception. +* `withMean`: False by default. Centers the data with mean before scaling. It will build a dense output, so take care when applying to sparse input. `StandardScaler` is an `Estimator` which can be `fit` on a dataset to produce a `StandardScalerModel`; this amounts to computing summary statistics. The model can then transform a `Vector` column in a dataset to have unit standard deviation and/or zero mean features. |