Seems what Feynman mentioned is the source code instead of documentation,
vectorMean is private, see
https://github.com/apache/spark/blob/v1.3.0/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixture.scala
At 2015-07-09 10:10:58, "诺铁" <noty...@gmail.com> wrote:
thanks, I understand now.
but I can't find mllib.clustering.GaussianMixture#vectorMean , what version
of spark do you use?
On Thu, Jul 9, 2015 at 1:16 AM, Feynman Liang <fli...@databricks.com> wrote:
A RDD[Double] is an abstraction for a large collection of doubles, possibly
distributed across multiple nodes. The DoubleRDDFunctions are there for
performing mean and variance calculations across this distributed dataset.
In contrast, a Vector is not distributed and fits on your local machine. You
would be better off computing these quantities on the Vector directly (see
mllib.clustering.GaussianMixture#vectorMean for an example of how to compute
the mean of a vector).
On Tue, Jul 7, 2015 at 8:26 PM, 诺铁 <noty...@gmail.com> wrote:
hi,
there are some useful functions in DoubleRDDFunctions, which I can use if I
have RDD[Double], eg, mean, variance.
Vector doesn't have such methods, how can I convert Vector to RDD[Double], or
maybe better if I can call mean directly on a Vector?
