[ https://issues.apache.org/jira/browse/MADLIB-1254?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16554743#comment-16554743 ]
Frank McQuillan commented on MADLIB-1254: ----------------------------------------- Other things to investigate: 1) when a categorical feature is dropped because it only has 1 level, the `_group` table is hard to read without additional information 2) what is the effect on predict with dropped features? Is it properly handled? > RF/DT: Grouping might give incorrect results if 1 group eliminates a > categorical variable > ----------------------------------------------------------------------------------------- > > Key: MADLIB-1254 > URL: https://issues.apache.org/jira/browse/MADLIB-1254 > Project: Apache MADlib > Issue Type: Bug > Components: Module: Decision Tree > Reporter: Rahul Iyer > Priority: Major > Fix For: v1.15 > > > If {{forest_train}} is run with grouping enabled and if one of the groups has > a categorical feature with just single level, then the categorical feature is > eliminated for that group. If other groups retain that feature, then the > output of impurity_var_importance is incorrect for the group in question. > There could be other ramifications related to this as well. > {code:java} > DROP TABLE IF EXISTS dt_golf CASCADE; > CREATE TABLE dt_golf ( > id integer NOT NULL, > "OUTLOOK" text, > temperature double precision, > humidity double precision, > "Cont_features" double precision[], > cat_features text[], > windy boolean, > class text > ) ; > INSERT INTO dt_golf > (id,"OUTLOOK",temperature,humidity,"Cont_features",cat_features, windy,class) > VALUES > (1, 'sunny', 85, 85,ARRAY[85, 85], ARRAY['a', 'b'], false, 'Don''t Play'), > (2, 'sunny', 80, 90, ARRAY[80, 90], ARRAY['a', 'b'], true, 'Don''t Play'), > (3, 'overcast', 83, 78, ARRAY[83, 78], ARRAY['a', 'b'], false, 'Play'), > (4, 'rain', 70, NULL, ARRAY[70, 96], ARRAY['a', 'b'], false, 'Play'), > (5, 'rain', 68, 80, ARRAY[68, 80], ARRAY['a', 'b'], false, 'Play'), > (6, 'rain', NULL, 70, ARRAY[65, 70], ARRAY['a', 'b'], true, 'Don''t Play'), > (7, 'overcast', 64, 65, ARRAY[64, 65], ARRAY['c', 'b'], NULL , 'Play'), > (8, 'sunny', 72, 95, ARRAY[72, 95], ARRAY['a', 'b'], false, 'Don''t Play'), > (9, 'sunny', 69, 70, ARRAY[69, 70], ARRAY['a', 'b'], false, 'Play'), > (10, 'rain', 75, 80, ARRAY[75, 80], ARRAY['a', 'b'], false, 'Play'), > (11, 'sunny', 75, 70, ARRAY[75, 70], ARRAY['a', 'd'], true, 'Play'), > (12, 'overcast', 72, 90, ARRAY[72, 90], ARRAY['c', 'b'], NULL, 'Play'), > (13, 'overcast', 81, 75, ARRAY[81, 75], ARRAY['a', 'b'], false, 'Play'), > (15, NULL, 81, 75, ARRAY[81, 75], ARRAY['a', 'b'], false, 'Play'), > (16, 'overcast', NULL, 75, ARRAY[81, 75], ARRAY['a', 'd'], false, 'Play'), > (14, 'rain', 71, 80, ARRAY[71, 80], ARRAY['c', 'b'], true, 'Don''t Play'); > DROP TABLE IF EXISTS train_output, train_output_summary, train_output_group, > train_output_poisson_count; > SELECT forest_train( > 'dt_golf', -- source table > 'train_output', -- output model table > 'id', -- id column > 'temperature::double precision', -- response > 'humidity, cat_features, windy, "Cont_features"', -- > features > NULL, -- exclude columns > 'class', -- grouping > 5, -- num of trees > NULL, -- num of random features > TRUE, -- importance > 20, -- num_permutations > 10, -- max depth > 1, -- min split > 1, -- min bucket > 3, -- number of bins per continuous variable > 'max_surrogates = 2 ', > FALSE > ); > \x on > SELECT * from train_output_summary; > SELECT * from train_output_group; > {code} > Results: > {code:java} > SELECT * from train_output_group; > -[ RECORD 1 > ]-----------+----------------------------------------------------------------------------- > gid | 1 > class | Don't Play > success | t > cat_n_levels | {2,2,2} > cat_levels_in_text | {c,a,True,False,c,a} > oob_error | 92.5335905349795 > oob_var_importance | {10.725,10.725,10.725,7.605,10.725,0} > impurity_var_importance | > {8.33148348160485,0,0,19.9999998625892,19.9999998625892,11.6685163809844} > -[ RECORD 2 > ]-----------+----------------------------------------------------------------------------- > gid | 2 > class | Play > success | t > cat_n_levels | {2,2} > cat_levels_in_text | {b,d,False,True} > oob_error | 43.0244073645405 > oob_var_importance | > {1.06581410364015e-15,1.06581410364015e-15,2.1326171875,16.019375,10.570875} > impurity_var_importance | > {0,0,0,37.8304000437732,38.4881698525677,23.6814277291654} > {code} > Note that the {{impurity_var_importance}} for {{gid=2}} has length 6 while > the {{oob_var_importance}} correctly has 5. -- This message was sent by Atlassian JIRA (v7.6.3#76005)