myui opened a new pull request #181: [HIVEMALL-233-2] RandomForest regressor accepts sparse vector input URL: https://github.com/apache/incubator-hivemall/pull/181 ## What changes were proposed in this pull request? Enable RandomForestRegressor to accept sparse vector input as RandomForestClassifier already does. This closes #178 ## What type of PR is it? Improvement ## What is the Jira issue? https://issues.apache.org/jira/browse/HIVEMALL-233 ## How was this patch tested? manual tests on EMR ## How to use this feature? ```sql with customers as ( select 1 as id, "male" as gender, 23 as age, "Japan" as country, 12 as num_purchases union all select 2 as id, "female" as gender, 43 as age, "US" as country, 4 as num_purchases union all select 3 as id, "other" as gender, 19 as age, "UK" as country, 2 as num_purchases union all select 4 as id, "male" as gender, 31 as age, "US" as country, 20 as num_purchases union all select 5 as id, "female" as gender, 37 as age, "Australia" as country, 9 as num_purchases ), training as ( select array_concat( quantitative_features( array("age"), age ), categorical_features( array("country", "gender"), country, gender ) ) as features, num_purchases from customers ) select train_randomforest_regressor( feature_hashing(features), -- feature vector num_purchases, -- target value '-trees 40 -seed 31' -- hyper-parameters ) from training ; ``` ## Checklist - [x] Did you apply source code formatter, i.e., `./bin/format_code.sh`, for your commit? - [ ] Did you run system tests on Hive (or Spark)?
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