1.1 - 8.10 - Calculation of prob_response and predict_confidence - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

The function calculates the values of prob_response and predict_confidence with the following formulas.

This is the formula for the value of class r:

valuer = Wr·X
where:
  • X is the vector of predictor values corresponding to an observation.
  • W r is the vector of predictor weights calculated by the model for class r, where r is a class specified by the Responses syntax element.

    To see the predictor weights, use the function SVMSparseSummary (ML Engine) or SVMDenseSummary (ML Engine), with OutputSummary ('false').

prob_response

For binary classification, the formula for the probability that a response belongs to class r is:

prob_response = sigmoid (valuer)

For multiple-class classification, the formula for the probability that a response belongs to class r is:

prob_response = softmaxr (values)

predict_confidence

The column predict_confidence, which appears only if you omit the Responses syntax element, displays the probability that the observation belongs to the class in the column predict_value. This value is the maximum value of prob_response over all responses r.