[jira] [Created] (MADLIB-1087) Random Forest fails if features are INT or NUMERIC only and variable importance is TRUE

["Paul Chang (JIRA)" <ji...@apache.org>]

Paul Chang created MADLIB-1087:
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             Summary: Random Forest fails if features are INT or NUMERIC only and variable importance is TRUE
                 Key: MADLIB-1087
                 URL: https://issues.apache.org/jira/browse/MADLIB-1087
             Project: Apache MADlib
          Issue Type: Bug
          Components: Module: Random Forest
            Reporter: Paul Chang


If we attempt to train on a dataset where all features are either INT or NUMERIC, and with variable importance TRUE, forest_train() fails with the following error:

[2017-04-03 13:35:35] [XX000] ERROR: plpy.SPIError: invalid array length (plpython.c:4648)
[2017-04-03 13:35:35] Detail: array_of_bigint: Size should be in [1, 1e7], 0 given
[2017-04-03 13:35:35] Where: Traceback (most recent call last):
[2017-04-03 13:35:35] PL/Python function "forest_train", line 42, in <module>
[2017-04-03 13:35:35] sample_ratio
[2017-04-03 13:35:35] PL/Python function "forest_train", line 591, in forest_train
[2017-04-03 13:35:35] PL/Python function "forest_train", line 1038, in _calculate_oob_prediction
[2017-04-03 13:35:35] PL/Python function "forest_train"

However, if we add a single feature column that is FLOAT, REAL, or DOUBLE PRECISION, the trainer does not fail.



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