Hi Tomasz,
The limitation will not be changed and you will found all the models
reference to SparkContext in the new Spark ML package. It make the Python
API simple for implementation.
But it does not means you can only call this function on local data, you
can operate this function on an RDD
Hi Yanbo,
thanks for info. Is it likely to change in (near :) ) future? Ability
to call this function only on local data (ie not in rdd) seems to be
rather serious limitation.
cheers,
Tomasz
On 02.01.2016 09:45, Yanbo Liang wrote:
Hi Tomasz,
The GMM is bind with the peer Java GMM
Hi Tomasz,
The GMM is bind with the peer Java GMM object, so it need reference to
SparkContext.
Some of MLlib(not ML) models are simple object such as KMeansModel,
LinearRegressionModel etc., but others will refer SparkContext. The later
ones and corresponding member functions should not called
Dear All,
I'm trying to implement a procedure that iteratively updates a rdd
using results from GaussianMixtureModel.predictSoft. In order to avoid
problems with local variable (the obtained GMM) beeing overwritten in
each pass of the loop I'm doing the following:
