Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 5

Logistic Regression

Logistic regression is a method for modeling the relationships between one or more explanatory variables and a categorical variable by expressing the posterior statistical distribution of the categorical variable via linear functions on observed data. If the categorical variable is binary, taking only two values, "0" and "1", the logistic regression is simple, otherwise, it is multinomial.

Note

For more information on the concepts behind the algorithm, see "Details" section.

For more information on the algorithm's parameters for a specific computation mode and examples of its usage, see "Batch Processing", "Online Processing" and "Distributed Processing" sections.