This example creates statistics using ScaleMap on a training data set and then
uses these statistics to scale a similar test data set.
Input
scale_housing_test
types |
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 "input" PARTITION BY ANY
ON scale_stat AS STATISTIC DIMENSION
USING
ScaleMethod ('midrange')
Accumulate ('id')
) AS dt;
Output
id |
price |
lotsize |
bedrooms |
bathrms |
stories |
11 |
1.06451612903226 |
1.30640668523677 |
1 |
1 |
-1 |
13 |
-1.64516129032258 |
-1.75766016713092 |
1 |
-1 |
-0.333333333333333 |
15 |
-1.21505376344086 |
-0.6991643454039 |
-1 |
-1 |
-1 |
12 |
-1.49462365591398 |
-1.03342618384401 |
-1 |
-1 |
-1 |
14 |
-1.25806451612903 |
-1.10027855153203 |
1 |
-1 |
-1 |