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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 geoHeil
, 9 months ago
[15:57:28] src/objective/regression_obj.cc:41: Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss Stack trace returned 2 entries: (0) 0 libxgboost4j5544838633935815740.dylib 0x000000012733ba99
via GitHub by superbobry
, 2 weeks ago
[17:28:25] src/objective/regression_obj.cc:41: Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss Stack trace returned 5 entries: (0) /tmp/libxgboost4j1912501567799701400.so
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
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$23.apply(RDD.scala:766) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:85) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745)