Ok, thanks for clarifying. So looks like numFeatures is only relevant for lib SVM format. I am using LabeledPoint, so if data is not sparse, perhaps numFeatures is not required. I thought that the Params class defines all the parameters passed to the ML algorithm. But it looks like it also includes other options. Just as a suggestion - it may be useful to have a separate class for just the algorithm parameters, so it is clear what can be tuned.
thanks -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Naive-Bayes-parameters-tp11592p11632.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
