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Posted to dev@ignite.apache.org by "Aleksey Zinoviev (JIRA)" <ji...@apache.org> on 2018/08/09 09:20:00 UTC
[jira] [Created] (IGNITE-9239) [ML] KMeansTrainer crashed if amount
of possible clusters more than amount of partitions in dataset
Aleksey Zinoviev created IGNITE-9239:
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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
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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
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