Like GLMPredict Example: Logistic Distribution Prediction, this example predicts the admission status of students. In both examples, the input column masters is categorical—the value can be yes or no. In the other example, the value is 'yes' or 'no'. In this example, the value is numerical—1 for yes or 0 for no—therefore, it must be cast to VARCHAR.
Input
- Input table: admissions_test_2, which has admissions information for 20 students
- Model: glm_admissions_model, output by "GLM Example: Logistic Regression Analysis with Intercept" in
Teradata Vantage™ Machine Learning Engine Analytic Function Reference, B700-4003, with the category column modified as follows:
attribute predictor category 1 masters '1' 2 masters '0'
id | masters | gpa | stats | programming | admitted |
---|---|---|---|---|---|
50 | 1 | 3.95000000000000E 000 | Beginner | Beginner | 0 |
51 | 1 | 3.76000000000000E 000 | Beginner | Beginner | 0 |
52 | 0 | 3.70000000000000E 000 | Novice | Beginner | 1 |
53 | 1 | 3.50000000000000E 000 | Beginner | Novice | 1 |
54 | 1 | 3.50000000000000E 000 | Beginner | Advanced | 1 |
55 | 0 | 3.60000000000000E 000 | Beginner | Advanced | 1 |
56 | 0 | 3.82000000000000E 000 | Advanced | Advanced | 1 |
57 | 0 | 3.71000000000000E 000 | Advanced | Advanced | 1 |
58 | 0 | 3.13000000000000E 000 | Advanced | Advanced | 1 |
59 | 0 | 3.65000000000000E 000 | Novice | Novice | 1 |
60 | 0 | 4.00000000000000E 000 | Advanced | Novice | 1 |
61 | 1 | 4.00000000000000E 000 | Advanced | Advanced | 1 |
62 | 0 | 3.70000000000000E 000 | Advanced | Advanced | 1 |
63 | 0 | 3.83000000000000E 000 | Advanced | Advanced | 1 |
64 | 1 | 3.81000000000000E 000 | Advanced | Advanced | 1 |
65 | 1 | 3.90000000000000E 000 | Advanced | Advanced | 1 |
66 | 0 | 3.87000000000000E 000 | Novice | Beginner | 1 |
67 | 1 | 3.46000000000000E 000 | Novice | Beginner | 0 |
68 | 0 | 1.87000000000000E 000 | Advanced | Novice | 1 |
69 | 0 | 3.96000000000000E 000 | Advanced | Advanced | 1 |
SQL Call
CREATE MULTISET TABLE glmpredict_admissions_2 AS (
SELECT * FROM GLMPredict (
ON (
SELECT id, CAST(masters AS varchar(10)) AS masters,
gpa, stats, programming, admitted
FROM admissions_test
) PARTITION BY ANY
ON glm_admissions_model AS Model DIMENSION
USING
Accumulate ('id','masters','gpa','stats','programming','admitted')
Family ('LOGISTIC')
LinkFunction ('LOGIT')
) AS dt
) WITH DATA;
Output
This query returns the following table:
SELECT * FROM glmpredict_admissions_2 ORDER BY 1;
Fitted values can vary in precision, because they depend on the model table output by ML Engine GLM function and fetched to Advanced SQL Engine.
id | masters | gpa | stats | programming | admitted | fitted value |
---|---|---|---|---|---|---|
50 | 1 | 3.95000000000000E 000 | Beginner | Beginner | 0 | 3.50763408888030E-001 |
51 | 1 | 3.76000000000000E 000 | Beginner | Beginner | 0 | 3.55708978581653E-001 |
52 | 0 | 3.70000000000000E 000 | Novice | Beginner | 1 | 7.58306140231079E-001 |
53 | 1 | 3.50000000000000E 000 | Beginner | Novice | 1 | 5.56012779663342E-001 |
54 | 1 | 3.50000000000000E 000 | Beginner | Advanced | 1 | 7.69474352959112E-001 |
55 | 0 | 3.60000000000000E 000 | Beginner | Advanced | 1 | 9.68031141480050E-001 |
56 | 0 | 3.82000000000000E 000 | Advanced | Advanced | 1 | 9.45772725968165E-001 |
57 | 0 | 3.71000000000000E 000 | Advanced | Advanced | 1 | 9.46411914806798E-001 |
58 | 0 | 3.13000000000000E 000 | Advanced | Advanced | 1 | 9.49666186386367E-001 |
59 | 0 | 3.65000000000000E 000 | Novice | Novice | 1 | 8.74189685344822E-001 |
60 | 0 | 4.00000000000000E 000 | Advanced | Novice | 1 | 8.65058992199339E-001 |
61 | 1 | 4.00000000000000E 000 | Advanced | Advanced | 1 | 6.50618727191735E-001 |
62 | 0 | 3.70000000000000E 000 | Advanced | Advanced | 1 | 9.46469669158547E-001 |
63 | 0 | 3.83000000000000E 000 | Advanced | Advanced | 1 | 9.45714262806374E-001 |
64 | 1 | 3.81000000000000E 000 | Advanced | Advanced | 1 | 6.55523357798207E-001 |
65 | 1 | 3.90000000000000E 000 | Advanced | Advanced | 1 | 6.53204164468356E-001 |
66 | 0 | 3.87000000000000E 000 | Novice | Beginner | 1 | 7.54738501228429E-001 |
67 | 1 | 3.46000000000000E 000 | Novice | Beginner | 0 | 2.60034297764359E-001 |
68 | 0 | 1.87000000000000E 000 | Advanced | Novice | 1 | 8.90965518431337E-001 |
69 | 0 | 3.96000000000000E 000 | Advanced | Advanced | 1 | 9.44948816395031E-001 |