SVMDensePredict Example 2: Polynomial Model - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.00
1.0
Published
May 2019
Language
English (United States)
Last Update
2019-11-22
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blj1506016597986.ditamap
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B700-4003
lifecycle
previous
Product Category
Teradata Vantage™

Input

The input table is iris_test (see SVMDense Examples Input).

SQL Call

SELECT * FROM SVMDensePredict (
  ON svm_iris_test AS "input" PARTITION BY ANY
  ON densesvm_iris_polynomial_model AS model DIMENSION
  USING
  IDColumn ('id')
  InputColumns ('[1:4]')
  Accumulate ('id', 'species')
) AS dt ORDER BY id;

Output

id predict_value predict_confidence species
5 setosa 1 setosa
10 setosa 1 setosa
15 setosa 1 setosa
20 setosa 1 setosa
25 setosa 1 setosa
30 setosa 1 setosa
35 setosa 1 setosa
40 setosa 1 setosa
45 setosa 1 setosa
50 setosa 1 setosa
55 virginica 1 versicolor
60 virginica 1 versicolor
65 setosa 1 versicolor
70 versicolor 1 versicolor
75 versicolor 1 versicolor
80 setosa 1 versicolor
85 virginica 1 versicolor
90 virginica 1 versicolor
95 virginica 1 versicolor
100 virginica 1 versicolor
105 virginica 1 virginica
110 virginica 1 virginica
115 virginica 1 virginica
120 virginica 1 virginica
125 virginica 1 virginica
130 virginica 1 virginica
135 virginica 1 virginica
140 virginica 1 virginica
145 virginica 1 virginica
150 virginica 1 virginica

The prediction accuracy with the polynomial model is 73.34%.