Aleksey Zinoviev created IGNITE-9239: ----------------------------------------
Summary: [ML] KMeansTrainer crashed if amount of possible clusters more than amount of partitions in dataset Key: IGNITE-9239 URL: https://issues.apache.org/jira/browse/IGNITE-9239 Project: Ignite Issue Type: Bug Components: ml Reporter: Aleksey Zinoviev Assignee: Aleksey Zinoviev How to reproduce? Set the K parameter in KMeans Trainer to 100, and run KMeansClusterization Example \ StackTrace is Exception in thread "KMeansClusterizationExample-#44" java.lang.RuntimeException: java.lang.IllegalArgumentException: bound must be positive at org.apache.ignite.ml.clustering.kmeans.KMeansTrainer.fit(KMeansTrainer.java:112) at org.apache.ignite.ml.clustering.kmeans.KMeansTrainer.fit(KMeansTrainer.java:46) at org.apache.ignite.ml.trainers.DatasetTrainer.fit(DatasetTrainer.java:68) at org.apache.ignite.examples.ml.clustering.KMeansClusterizationExample.lambda$main$0(KMeansClusterizationExample.java:60) at java.lang.Thread.run(Thread.java:745) Caused by: java.lang.IllegalArgumentException: bound must be positive at java.util.Random.nextInt(Random.java:388) at org.apache.ignite.ml.clustering.kmeans.KMeansTrainer.initClusterCentersRandomly(KMeansTrainer.java:193) at org.apache.ignite.ml.clustering.kmeans.KMeansTrainer.fit(KMeansTrainer.java:86) ... 4 more The possible solution : correct the mechanism of rndPnts computation in the row 180-190 in KMeansTrainer -- This message was sent by Atlassian JIRA (v7.6.3#76005)