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Posted to issues@madlib.apache.org by "Frank McQuillan (JIRA)" <ji...@apache.org> on 2016/03/09 01:14:40 UTC
[jira] [Resolved] (MADLIB-584) SVM: Training on small table will
lead support vector failure in parallel mode
[ https://issues.apache.org/jira/browse/MADLIB-584?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Frank McQuillan resolved MADLIB-584.
------------------------------------
Resolution: Fixed
fixed by new 1.9 algo
> SVM: Training on small table will lead support vector failure in parallel mode
> ------------------------------------------------------------------------------
>
> Key: MADLIB-584
> URL: https://issues.apache.org/jira/browse/MADLIB-584
> Project: Apache MADlib
> Issue Type: Bug
> Reporter: Jiali Yao
> Assignee: Rahul Iyer
> Fix For: v1.9
>
>
> 0. Prepare data
> {code}
> drop table if exists svm_input;
> CREATE TABLE svm_input(id int, ind FLOAT8[],label float8);
> insert into svm_input values(1, '{1,1}', 2);
> insert into svm_input values(2, '{1,2}', -2);
> {code}
> 1. svm_novelty_detection
> {code}
> madlib=# SELECT madlib.svm_novelty_detection('svm_input', 'svm_model', true, 'madlib.svm_dot');
> ERROR: plpy.SPIError: plpy.SPIError: plpy.Error: No support vector model with name svm_model0 found. (plpython.c:4648)
> CONTEXT: Traceback (most recent call last):
> PL/Python function "svm_novelty_detection", line 28, in <module>
> return online_sv.svm_novelty_detection( MADlibSchema, input_table, model_table, parallel, kernel_func);
> PL/Python function "svm_novelty_detection", line 204, in svm_novelty_detection
> PL/Python function "svm_novelty_detection"
> {code}
> 2. svm_regresssion
> {code}
> madlib=# SELECT madlib.svm_regression('svm_input', 'svm_model', true, 'madlib.svm_dot');
> ERROR: plpy.SPIError: plpy.SPIError: plpy.Error: No support vector model with name svm_model0 found. (plpython.c:4648)
> CONTEXT: Traceback (most recent call last):
> PL/Python function "svm_regression", line 28, in <module>
> return online_sv.svm_regression( MADlibSchema, input_table, model_table, parallel, kernel_func);
> PL/Python function "svm_regression", line 53, in svm_regression
> PL/Python function "svm_regression"
> {code}
> 3. svm_classification
> {code}
> madlib=# SELECT madlib.svm_classification('svm_input', 'svm_model', true, 'madlib.svm_dot');
> ERROR: plpy.SPIError: plpy.SPIError: plpy.Error: No support vector model with name svm_model0 found. (plpython.c:4648)
> CONTEXT: Traceback (most recent call last):
> PL/Python function "svm_classification", line 28, in <module>
> return online_sv.svm_classification( MADlibSchema, input_table, model_table, parallel, kernel_func);
> PL/Python function "svm_classification", line 129, in svm_classification
> PL/Python function "svm_classification"
> {code}
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