akshaybhatt14495

@kaushikacharya thanks for response, actually i need k nearest neighbors (KNN) , so for that do we need classification in dataset (i.e. first entry in each case as 0 or...

@kaushikacharya i'm talking about KNN.scala

Got another error in command knn.fit(training) Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Column features must be of type org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7 but was actually org.apache.spark.mllib.linalg.VectorUDT@f71b0bce. at scala.Predef$.require(Predef.scala:224) at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:42) at org.apache.spark.ml.PredictorParams$class.validateAndTransformSchema(Predictor.scala:51)...

@kaushikacharya spark version is 2.2.0

i changed my version and now working with spark 2.1.0, then also got same error,

Ok, i used MLUtils function convertVectorColumnsFromML(training, "features") so then got new error for sample data given in sample_libsvm_data.txt java.lang.IllegalArgumentException: requirement failed: Sampling fraction (1.01) must be on interval [0, 1]...

same issue when i chose euclidian type, in case of hamming , i got result but showing result distance as zero in all case

And while running algo with datapoints with same coordinates , it is throwing an exception java.lang.NoSuchMethodError: org.apache.spark.mllib.linalg.Vector.toBreeze()Lbreeze/linalg/Vector; at org.apache.spark.mllib.linalg.LinalgShim$.toBreeze(LinalgShim.scala:32) at com.github.karlhigley.spark.neighbors.linalg.EuclideanDistance$.compute(DistanceMeasure.scala:47) at com.github.karlhigley.spark.neighbors.ANNModel$$anonfun$computeDistances$2$$anonfun$apply$6$$anonfun$apply$9.apply(ANNModel.scala:91) at com.github.karlhigley.spark.neighbors.ANNModel$$anonfun$computeDistances$2$$anonfun$apply$6$$anonfun$apply$9.apply(ANNModel.scala:89) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) at scala.collection.Iterator$$anon$12.next(Iterator.scala:444) at...