Re: error in mllib lr example code
Thanks Xiangrui, Matei and Arpit. It does work fine after adding
Vector.dense. I have a follow up question, I will post on a new thread.
On Thu, Apr 24, 2014 at 2:49 AM, Arpit Tak wrote:
> Also try out these examples, all of them works
>
> http://docs.sigmoidanalytics.com/index.php/MLlib
>
> if you spot any problems in those, let us know.
>
> Regards,
> arpit
>
>
> On Wed, Apr 23, 2014 at 11:08 PM, Matei Zaharia
> wrote:
>
>> 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 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
>> wrote:
>> >>
>> >> sorry...added a subject now
>> >>
>> >> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi
>> 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)
>> >>>
>> >>> }
>> >>>
>> >>> ..
>> >>>
>> >>> }
>> >>>
>> >>> 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
>> >>
>> >>
>>
>>
>
Re: error in mllib lr example code
Also try out these examples, all of them works
http://docs.sigmoidanalytics.com/index.php/MLlib
if you spot any problems in those, let us know.
Regards,
arpit
On Wed, Apr 23, 2014 at 11:08 PM, Matei Zaharia wrote:
> 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 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
> wrote:
> >>
> >> sorry...added a subject now
> >>
> >> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi
> 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)
> >>>
> >>> }
> >>>
> >>> ..
> >>>
> >>> }
> >>>
> >>> 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
> >>
> >>
>
>
Re: error in mllib lr example code
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 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 wrote:
>>
>> sorry...added a subject now
>>
>> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi 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)
>>>
>>> }
>>>
>>> ..
>>>
>>> }
>>>
>>> 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
>>
>>
Re: error in mllib lr example code
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 wrote:
>
> sorry...added a subject now
>
> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi 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)
>>
>> }
>>
>> ..
>>
>> }
>>
>> 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
>
>
error in mllib lr example code
sorry...added a subject now
On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi 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)
>
> }
>
> ..
>
> }
>
> 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
>
