Hi,
I am running linear regression on a dataframe and get the following error:
Exception in thread "main" java.lang.AssertionError: assertion failed:
Training dataset is empty.
at scala.Predef$.assert(Predef.scala:170)
at
org.apache.spark.ml.optim.WeightedLeastSquares$Aggregator.validate(WeightedLeastSquares.scala:247)
at
org.apache.spark.ml.optim.WeightedLeastSquares.fit(WeightedLeastSquares.scala:82)
at
org.apache.spark.ml.regression.LinearRegression.train(LinearRegression.scala:180)
at
org.apache.spark.ml.regression.LinearRegression.train(LinearRegression.scala:70)
at org.apache.spark.ml.Predictor.fit(Predictor.scala:90)
here is the data and code:
{"label":79.3,"features":{"type":1,"values":[6412.143500000001,888.0,1407.0,1.5844594594594594,10.614,12.07,0.12062966031483012,0.9991237664152219,6.065,0.49751449875724935]}}
{"label":72.3,"features":{"type":1,"values":[6306.044500000001,1084.0,1451.0,1.338560885608856,7.018,12.04,0.41710963455149497,0.9992054343916128,6.05,0.4975083056478405]}}
{"label":76.7,"features":{"type":1,"values":[6142.920000000003,1494.0,1437.0,0.9618473895582329,7.939,12.06,0.34170812603648426,0.9992216101762574,6.06,0.49751243781094534]}}
val lr = new LinearRegression().setMaxIter(300).setFeaturesCol("features")
val lrModel = lr.fit(assembleddata)
Any clue or inputs are appreciated.
Regards,
Shawn
