hi Xiangrui,
I am trying to implement the tfidf as per the instruction you sent in
your response to Jatin.
I am getting an error in idf step. Here are my steps that run till the last
line where the compile
fails.
val labeledDocs = sc.textFile("title_subcategory")
val stopwords = scala.io.Source.fromFile("stopwords.txt").getLines().toList
val labeledTerms =
labeledDocs.map(_.split('\t')).map(x=>(x(2).toDouble,x(1).split('
').map(_.toLowerCase).filter(!stopwords.contains(_)).toSeq))
val tf = new HashingTF()
val freqs = labeledTerms.map(x=>(x._1,tf.transform(x._2)))
val idf = new IDF()
val idfModel = idf.fit(freqs.values)
val vectors = freqs.map(x => LabeledPoint(x._1, idfModel.transform(x._2)))
This is where it fails with the following error:
NBContentSubcategory.scala:39: error: overloaded method value transform with
alternatives:
(dataset:
org.apache.spark.api.java.JavaRDD[org.apache.spark.mllib.linalg.Vector])org.apache.spark.api.java.JavaRDD[org.apache.spark.mllib.linalg.Vector]
<and>
(dataset:
org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector])org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector]
cannot be applied to (org.apache.spark.mllib.linalg.Vector)
val transformedValues = idfModel.transform(values)
It seems to be getting confused with multiple (java and scala) transform
methods.
Any insights?
Thanks,
Nilesh
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