gradient: The gradient of the objective function

In Beuleup93/dgrGlm: Regression logistic binary tools

Description

The gradient function represents the partial derivative of the cost function with respect to each coefficient of the model

Usage

gradient(theta, X, y)

Arguments

theta	is a vector containing the parameters or coefficient of the logistic to be estimated
X	is the matrix of our predictor variables with the bias column
y	is a target variable to predict

Value

this function returns a gradient vector

Author(s)

"Saliou NDAO [e-mail]"

Examples

## Not run: 
  gradient(theta, X, y)

## End(Not run)

Beuleup93/dgrGlm documentation built on Dec. 17, 2021, 10:50 a.m.