Understanding Logistic Regression in C#

The Logistic regression is a linear model used for binomial regression. It is used in medical science and to predict a customer’s tendency to purchase a product. It makes use of predictor variables for this purpose.

Logistic Regression allows easier analysis of results in the form of odds ratios and statistical hypothesis testing.

A generalized linear model has taken input for a non-linear link function. The linear model has the following form −

z = c1x1 + c2x2 + … cnxn + i = ct x + i

Here,

c is the coefficient vector,
i is the intercept value
x is the observation vector