This example creates statistics using ScaleMap on a training data set and then uses these statistics to scale a similar test data set.
Input
- Training data: scale_housing, as in Scale Example: ScaleMethod ('midrange')
- Test data: scale_housing_test
type | id | price | lotsize | bedrooms | bathrms | stories |
---|---|---|---|---|---|---|
bungalow | 11 | 90000 | 7200 | 3 | 2 | 1 |
classic | 12 | 30500 | 3000 | 2 | 1 | 1 |
classic | 13 | 27000 | 1700 | 3 | 1 | 2 |
classic | 14 | 36000 | 2880 | 3 | 1 | 1 |
classic | 15 | 37000 | 3600 | 2 | 1 | 1 |
SQL Call to Create Statistics Table from Training Data
CREATE multiset table scale_stat AS ( SELECT * FROM ScaleMap ( ON scale_housing USING TargetColumns('[2:6]') MissValue ('omit') ) AS dt ) WITH DATA;
SQL Call to Scale Test Data
SELECT * FROM Scale ( ON scale_housing_test AS InputTable PARTITION BY ANY ON scale_stat AS statistic DIMENSION USING ScaleMethod ('midrange') Accumulate ('id') ) AS dt ORDER BY id,price,lotsize;
Output
id price lotsize bedrooms bathrms stories -- ------------------- ------------------- -------- ------- ------------------- 11 1.064516129032258 1.3064066852367688 1.0 1.0 -1.0 12 -1.4946236559139785 -1.033426183844011 -1.0 -1.0 -1.0 13 -1.6451612903225807 -1.7576601671309193 1.0 -1.0 -0.3333333333333333 14 -1.2580645161290323 -1.1002785515320335 1.0 -1.0 -1.0 15 -1.2150537634408602 -0.6991643454038997 -1.0 -1.0 -1.0
Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.