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Posted to issues@madlib.apache.org by "Rahul Iyer (JIRA)" <ji...@apache.org> on 2018/03/22 17:31:00 UTC
[jira] [Assigned] (MADLIB-1218) DT and RF: categorical levels
reported incorrectly when grouping is used
[ https://issues.apache.org/jira/browse/MADLIB-1218?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rahul Iyer reassigned MADLIB-1218:
----------------------------------
Assignee: Rahul Iyer (was: Rahul Iyer)
> DT and RF: categorical levels reported incorrectly when grouping is used
> -------------------------------------------------------------------------
>
> Key: MADLIB-1218
> URL: https://issues.apache.org/jira/browse/MADLIB-1218
> Project: Apache MADlib
> Issue Type: Bug
> Components: Module: Decision Tree, Module: Random Forest
> Reporter: Frank McQuillan
> Assignee: Rahul Iyer
> Priority: Major
> Fix For: v1.14
>
>
> {code}
> DROP TABLE IF EXISTS mt_cars;
> CREATE TABLE mt_cars (
> id integer NOT NULL,
> mpg double precision,
> cyl integer,
> disp double precision,
> hp integer,
> drat double precision,
> wt double precision,
> qsec double precision,
> vs integer,
> am integer,
> gear integer,
> carb integer
> );
> INSERT INTO mt_cars VALUES
> (1,18.7,8,360,175,3.15,3.44,17.02,0,0,3,2),
> (2,21,6,160,110,3.9,2.62,16.46,0,1,4,4),
> (3,24.4,4,146.7,62,3.69,3.19,20,1,0,4,2),
> (4,21,6,160,110,3.9,2.875,17.02,0,1,4,4),
> (5,17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4),
> (6,16.4,8,275.8,180,3.078,4.07,17.4,0,0,3,3),
> (7,22.8,4,108,93,3.85,2.32,18.61,1,1,4,1),
> (8,17.3,8,275.8,180,3.078,3.73,17.6,0,0,3,3),
> (9,21.4,null,258,110,3.08,3.215,19.44,1,0,3,1),
> (10,15.2,8,275.8,180,3.078,3.78,18,0,0,3,3),
> (11,18.1,6,225,105,2.768,3.46,20.22,1,0,3,1),
> (12,32.4,4,78.7,66,4.08,2.20,19.47,1,1,4,1),
> (13,14.3,8,360,245,3.21,3.578,15.84,0,0,3,4),
> (14,22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2),
> (15,30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2),
> (16,19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4),
> (17,33.9,4,71.14,65,4.22,1.835,19.9,1,1,4,1),
> (18,15.2,null,304,150,3.15,3.435,17.3,0,0,3,2),
> (19,10.4,8,472,205,2.93,5.25,17.98,0,0,3,4),
> (20,27.3,4,79,66,4.08,1.935,18.9,1,1,4,1),
> (21,10.4,8,460,215,3,5.424,17.82,0,0,3,4),
> (22,26,4,120.3,91,4.43,2.14,16.7,0,1,5,2),
> (23,14.7,8,440,230,3.23,5.345,17.42,0,0,3,4),
> (24,30.4,4,95.14,113,3.77,1.513,16.9,1,1,5,2),
> (25,21.5,4,120.1,97,3.70,2.465,20.01,1,0,3,1),
> (26,15.8,8,351,264,4.22,3.17,14.5,0,1,5,4),
> (27,15.5,8,318,150,2.768,3.52,16.87,0,0,3,2),
> (28,15,8,301,335,3.54,3.578,14.6,0,1,5,8),
> (29,13.3,8,350,245,3.73,3.84,15.41,0,0,3,4),
> (30,19.2,8,400,175,3.08,3.845,17.05,0,0,3,2),
> (31,19.7,6,145,175,3.62,2.77,15.5,0,1,5,6),
> (32,21.4,4,121,109,4.11,2.78,18.6,1,1,4,2);
> {code}
> RF:
> {code}
> DROP TABLE IF EXISTS mt_cars_output, mt_cars_output_group, mt_cars_output_summary;
> SELECT madlib.forest_train('mt_cars',
> 'mt_cars_output',
> 'id',
> 'mpg',
> '*',
> 'id, hp, drat, am, gear, carb', -- exclude columns
> 'am', -- grouping
> 10::integer,
> 2::integer,
> TRUE::boolean,
> 1,
> 10,
> 8,
> 3,
> 10
> );
> SELECT * FROM mt_cars_output_summary;
> {code}
> produces
> {code}
> -[ RECORD 1 ]---------+-----------------------------------------------------------------------
> method | forest_train
> is_classification | f
> source_table | mt_cars
> model_table | mt_cars_output
> id_col_name | id
> dependent_varname | mpg
> independent_varnames | vs,cyl,disp,qsec,wt
> cat_features | vs,cyl
> con_features | disp,qsec,wt
> grouping_cols | am
> num_trees | 10
> num_random_features | 2
> max_tree_depth | 10
> min_split | 8
> min_bucket | 3
> num_splits | 10
> verbose | f
> importance | t
> num_permutations | 1
> num_all_groups | 2
> num_failed_groups | 0
> total_rows_processed | 32
> total_rows_skipped | 0
> dependent_var_levels |
> dependent_var_type | double precision
> independent_var_types | integer, integer, double precision, double precision, double precision
> null_proxy | None
> {code}
> {code}
> SELECT * FROM mt_cars_output_group;
> {code}
> produces
> {code}
> -[ RECORD 1 ]------+--------------------------------------
> gid | 1
> am | 0
> success | t
> cat_n_levels | {3,3}
> cat_levels_in_text | {4,6,8,4,6,8}
> oob_error | 10.4384609425616
> cat_var_importance | {1.77200744569228,3.23893136930339}
> con_var_importance | {6.52806304913008,0,2.71255870662522}
> -[ RECORD 2 ]------+--------------------------------------
> gid | 2
> am | 1
> success | t
> cat_n_levels | {2,2}
> cat_levels_in_text | {0,1,0,1}
> oob_error | 22.3349978333876
> cat_var_importance | {4.59597959183674,0}
> con_var_importance | {5.715875,0,18.4067344897959}
> {code}
> In the above, cat_n_levels and cat_levels_in_text are wrong. I would expect {0,1,4,6,8} to be reported for both groups.
> Compare the above with the case of no groups:
> {code}
> DROP TABLE IF EXISTS mt_cars_output, mt_cars_output_group, mt_cars_output_summary;
> SELECT madlib.forest_train('mt_cars',
> 'mt_cars_output',
> 'id',
> 'mpg',
> '*',
> 'id, hp, drat, am, gear, carb', -- exclude columns
> NULL, -- no groups
> 10::integer,
> 2::integer,
> TRUE::boolean,
> 1,
> 10,
> 8,
> 3,
> 10
> );
> SELECT * FROM mt_cars_output_summary;
> {code}
> produces
> {code}
> [ RECORD 1 ]---------+-----------------------------------------------------------------------
> method | forest_train
> is_classification | f
> source_table | mt_cars
> model_table | mt_cars_output
> id_col_name | id
> dependent_varname | mpg
> independent_varnames | vs,cyl,disp,qsec,wt
> cat_features | vs,cyl
> con_features | disp,qsec,wt
> grouping_cols |
> num_trees | 10
> num_random_features | 2
> max_tree_depth | 10
> min_split | 8
> min_bucket | 3
> num_splits | 10
> verbose | f
> importance | t
> num_permutations | 1
> num_all_groups | 1
> num_failed_groups | 0
> total_rows_processed | 32
> total_rows_skipped | 0
> dependent_var_levels |
> dependent_var_type | double precision
> independent_var_types | integer, integer, double precision, double precision, double precision
> null_proxy | None
> {code}
> SELECT * FROM mt_cars_output_group;
> produces:
> gid | 1
> success | t
> cat_n_levels | {2,3}
> cat_levels_in_text | {0,1,4,6,8}
> oob_error | 9.90200731761036
> cat_var_importance | {0.390353827160495,12.8836927689546}
> con_var_importance | {0.118665925451092,0.947886524555693,19.910665401879}
> which seems OK.
> DT:
> I am seeing the same thing with decision tree. Here is a sample output grouping on 'am' from decision tree:
> {code}
> madlib=# SELECT am, pruning_cp, cat_levels_in_text, cat_n_levels, tree_depth FROM train_output;
> -[ RECORD 1 ]------+--------------
> am | 1
> pruning_cp | 0
> cat_levels_in_text | {0,1,0,1}
> cat_n_levels | {2,2}
> tree_depth | 1
> -[ RECORD 2 ]------+--------------
> am | 0
> pruning_cp | 0
> cat_levels_in_text | {4,6,8,4,6,8}
> cat_n_levels | {3,3}
> tree_depth | 3
> {code}
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