See http://people.csail.mit.edu/matei/spark-unified-docs/ for a more recent build of the docs; if you spot any problems in those, let us know.
Matei On Apr 23, 2014, at 9:49 AM, Xiangrui Meng <men...@gmail.com> wrote: > The doc is for 0.9.1. You are running a later snapshot, which added > sparse vectors. Try LabeledPoint(parts(0).toDouble, > Vectors.dense(parts(1).split(' ').map(x => x.toDouble)). The examples > are updated in the master branch. You can also check the examples > there. -Xiangrui > > On Wed, Apr 23, 2014 at 9:34 AM, Mohit Jaggi <mohitja...@gmail.com> wrote: >> >> sorry...added a subject now >> >> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi <mohitja...@gmail.com> wrote: >>> >>> I am trying to run the example linear regression code from >>> >>> http://spark.apache.org/docs/latest/mllib-guide.html >>> >>> But I am getting the following error...am I missing an import? >>> >>> ----code---- >>> >>> import org.apache.spark._ >>> >>> import org.apache.spark.mllib.regression.LinearRegressionWithSGD >>> >>> import org.apache.spark.mllib.regression.LabeledPoint >>> >>> >>> object ModelLR { >>> >>> def main(args: Array[String]) { >>> >>> val sc = new SparkContext(args(0), "SparkLR", >>> >>> System.getenv("SPARK_HOME"), >>> SparkContext.jarOfClass(this.getClass).toSeq) >>> >>> // Load and parse the data >>> >>> val data = sc.textFile("mllib/data/ridge-data/lpsa.data") >>> >>> val parsedData = data.map { line => >>> >>> val parts = line.split(',') >>> >>> LabeledPoint(parts(0).toDouble, parts(1).split(' ').map(x => >>> x.toDouble).toArray) >>> >>> } >>> >>> ...<snip>... >>> >>> } >>> >>> ----error---- >>> >>> - polymorphic expression cannot be instantiated to expected type; found : >>> [U >: Double]Array[U] required: >>> >>> org.apache.spark.mllib.linalg.Vector >>> >>> - polymorphic expression cannot be instantiated to expected type; found : >>> [U >: Double]Array[U] required: >>> >>> org.apache.spark.mllib.linalg.Vector >> >>