Hi, I have built the logistic regression model using training-dataset. When I am predicting on a test-dataset, it is throwing the below error of size mismatch.
Steps done: 1. String indexers on categorical features. 2. One hot encoding on these indexed features. Any help is appreciated to resolve this issue or is it a bug ? SparkException: *Job aborted due to stage failure: Task 0 in stage 635.0 failed 1 times, most recent failure: Lost task 0.0 in stage 635.0 (TID 19421, localhost): java.lang.IllegalArgumentException: requirement failed: BLAS.dot(x: Vector, y:Vector) was given Vectors with non-matching sizes: x.size = 15909, y.size = 29471* at scala.Predef$.require(Predef.scala:224) at org.apache.spark.ml.linalg.BLAS$.dot(BLAS.scala:104) at org.apache.spark.ml.classification.LogisticRegressionModel$$anonfun$19.apply(LogisticRegression.scala:505) at org.apache.spark.ml.classification.LogisticRegressionModel$$anonfun$19.apply(LogisticRegression.scala:504) at org.apache.spark.ml.classification.LogisticRegressionModel.predictRaw(LogisticRegression.scala:594) at org.apache.spark.ml.classification.LogisticRegressionModel.predictRaw(LogisticRegression.scala:484) at org.apache.spark.ml.classification.ProbabilisticClassificationModel$$anonfun$1.apply(ProbabilisticClassifier.scala:112) at org.apache.spark.ml.classification.ProbabilisticClassificationModel$$anonfun$1.apply(ProbabilisticClassifier.scala:111) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.evalExpr137$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
