Thanks a lot! Can I ask why this code generates a uniform distribution? If dist is N(0,1) data should be N(-1, 2).
Let me know. Thanks, Luca 2015-02-07 3:00 GMT+00:00 Burak Yavuz <brk...@gmail.com>: > Hi, > > You can do the following: > ``` > import org.apache.spark.mllib.linalg.distributed.RowMatrix > import org.apache.spark.mllib.random._ > > // sc is the spark context, numPartitions is the number of partitions you > want the RDD to be in > val dist: RDD[Vector] = RandomRDDs.normalVectorRDD(sc, n, k, > numPartitions, seed) > // make the distribution uniform between (-1, 1) > val data = dist.map(_ * 2 - 1) > val matrix = new RowMatrix(data, n, k) > On Feb 6, 2015 11:18 AM, "Donbeo" <lucapug...@gmail.com> wrote: > >> Hi >> I would like to know how can I generate a random matrix where each element >> come from a uniform distribution in -1, 1 . >> >> In particular I would like the matrix be a distributed row matrix with >> dimension n x p >> >> Is this possible with mllib? Should I use another library? >> >> >> >> -- >> View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/generate-a-random-matrix-with-uniform-distribution-tp21538.html >> Sent from the Apache Spark User List mailing list archive at Nabble.com. >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> >>
