ArrayIndexOutOfBoundsException & java.lang.NullPointerException

[SpongebBob]

I encountered this problem with my own features in the Kaggle of Quora、

Exception in thread "Thread-6" java.lang.ArrayIndexOutOfBoundsException: 750
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3002)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3038)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3042)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3042)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3038)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3038)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3038)
at ml.Tree.DecisionTreeRegressor.expand_node(DecisionTreeRegressor.java:3038)
at ml.Tree.DecisionTreeRegressor.fit(DecisionTreeRegressor.java:2382)
at ml.Tree.DecisionTreeRegressor.run(DecisionTreeRegressor.java:483)
at java.lang.Thread.run(Thread.java:745)
Exception in thread "Thread-3" java.lang.NullPointerException
at ml.Tree.DecisionTreeRegressor.isfitted(DecisionTreeRegressor.java:3275)
at ml.Tree.scoringhelperv2.(scoringhelperv2.java:107)
at ml.Tree.RandomForestRegressor.predict2d(RandomForestRegressor.java:744)
at ml.Tree.GradientBoostingForestClassifier.fit(GradientBoostingForestClassifier.java:2353)
at ml.Tree.GradientBoostingForestClassifier.run(GradientBoostingForestClassifier.java:382)
at java.lang.Thread.run(Thread.java:745)
Exception in thread "Thread-1112" java.lang.ArrayIndexOutOfBoundsException: 983
at ml.Tree.DecisionTreeClassifier.expand_node(DecisionTreeClassifier.java:3185)
at ml.Tree.DecisionTreeClassifier.expand_node(DecisionTreeClassifier.java:3225)
at ml.Tree.DecisionTreeClassifier.expand_node(DecisionTreeClassifier.java:3225)
at ml.Tree.DecisionTreeClassifier.expand_node(DecisionTreeClassifier.java:3221)
at ml.Tree.DecisionTreeClassifier.expand_node(DecisionTreeClassifier.java:3225)
at ml.Tree.DecisionTreeClassifier.fit(DecisionTreeClassifier.java:2576)
at ml.Tree.DecisionTreeClassifier.run(DecisionTreeClassifier.java:537)
at java.lang.Thread.run(Thread.java:745)
Exception in thread "Thread-1137" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-1617" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-1642" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2075" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2284" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2365" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2382" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2463" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2608" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2721" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2802" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2883" java.lang.ArrayIndexOutOfBoundsException
Exception in thread "Thread-2996" java.lang.ArrayIndexOutOfBoundsException
logloss : 0.257352525104832
logloss : 2.4462523363834303
Exception in thread "main" java.lang.NullPointerException
at ml.Tree.DecisionTreeClassifier.isfitted(DecisionTreeClassifier.java:3458)
at ml.Tree.scoringhelpercatv2.(scoringhelpercatv2.java:107)
at ml.Tree.RandomForestClassifier.predict_proba(RandomForestClassifier.java:795)
at ml.stacknet.StackNetClassifier.fit(StackNetClassifier.java:3532)
at stacknetrun.runstacknet.main(runstacknet.java:437)

I am sure that there is no zero like 0.000000 in the sparse file and all the data is in order。
what's more, I have 489 features. Is it too much?
/(ㄒoㄒ)/~~

[xiaofeifei1800]

Same issue

[xiaofeifei1800]

@SpongebBob Does it generate querry_pred.csv file? I can't find it.

[kaz-Anova]

Could you care to re-test with the new version?

[xiaofeifei1800]

I will try today and let you know

[SpongebBob]

@kaz-Anova I add rounding=30 to the tree based model, the bug is gone!

[SpongebBob]

@xiaofeifei1800 If you use tree based model, try to add param rounding. It worked for me.