Searched on Google with the first line of a JAVA stack trace?

We can recommend more relevant solutions and speed up debugging when you paste your entire stack trace with the exception message. Try a sample exception.

Recommended solutions based on your search

Solutions on the web

via GitHub by geoHeil
, 1 year ago
[14:43:22] src/metric/elementwise_metric.cc:28: Check failed: (preds.size()) == (info.labels.size()) label and prediction size not match, hint: use merror or mlogloss for multi-class classification
via GitHub by penolove
, 1 year ago
[15:57:17] src/data/data.cc:51: Check failed: (version) == (kVersion) MetaInfo: invalid format
via GitHub by greghor
, 1 year ago
[15:43:58] src/io/local_filesys.cc:154: Check failed: allow_null LocalFileSystem: fail to open "/Users/greghor/anaconda2/lib/python2.7/site-packages/xgboost/jvm-packages/xgboost4j-example/src/main/scala/ml/dmlc/xgboost4j/scala/example/./model/dump.raw.txt"
via GitHub by greghor
, 1 year ago
[09:25:39] src/io/local_filesys.cc:86: LocalFileSystem.ListDirectory ../../demo/data error: No such file or directory
via GitHub by futurecam
, 2 years ago
[21:23:06] src/learner.cc:283: Check failed: ModelInitialized() Always call InitModel or LoadModel before update
via GitHub by futurecam
, 2 years ago
[21:23:06] src/learner.cc:283: Check failed: ModelInitialized() Always call InitModel or LoadModel before update
ml.dmlc.xgboost4j.java.XGBoostError: [14:43:22] src/metric/elementwise_metric.cc:28: Check failed: (preds.size()) == (info.labels.size()) label and prediction size not match, hint: use merror or mlogloss for multi-class classification at ml.dmlc.xgboost4j.java.JNIErrorHandle.checkCall(JNIErrorHandle.java:48) at ml.dmlc.xgboost4j.java.Booster.evalSet(Booster.java:178) at ml.dmlc.xgboost4j.scala.Booster.evalSet(Booster.scala:97) at ml.dmlc.xgboost4j.scala.spark.XGBoostModel$$anonfun$1.apply(XGBoostModel.scala:80) at ml.dmlc.xgboost4j.scala.spark.XGBoostModel$$anonfun$1.apply(XGBoostModel.scala:62) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:766) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:766) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)