Project features onto principal components
Project features onto principal components
sdf_project( object, newdata, features = dimnames(object$pc)[[1]], feature_prefix = NULL, ... )
object |
A Spark PCA model object |
newdata |
An object coercible to a Spark DataFrame |
features |
A vector of names of columns to be projected |
feature_prefix |
The prefix used in naming the output features |
... |
Optional arguments; currently unused. |
The family of functions prefixed with sdf_ generally access the Scala
Spark DataFrame API directly, as opposed to the dplyr interface which
uses Spark SQL. These functions will 'force' any pending SQL in a
dplyr pipeline, such that the resulting tbl_spark object
returned will no longer have the attached 'lazy' SQL operations. Note that
the underlying Spark DataFrame does execute its operations lazily, so
that even though the pending set of operations (currently) are not exposed at
the R level, these operations will only be executed when you explicitly
collect() the table.
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.