Chapter. Logistic Regression

What is logistic regression?

Logistic regression is a statistical analysis method used to predict a data value based on prior observations of a data set. A logistic regression model predicts a dependent data variable by analyzing the relationship between one or more existing independent variables.

The dependent variable of logistics regression can be two-category or multi-category, but the two-category is more common and easier to explain. So the most common use in practice is the logistics of the two classifications. An example used by TensorFlow.NET is a hand-written digit recognition, which is a multi-category.

Softmax regression allows us to handle _static%5Clogistic-regression%5C1557035393445.png1557035393445 where K is the number of classes.

The full example is here.