BGD: Batch Gradient Descent

In Sakoylf/StatComp21088: Mini-batch Gradient Descent

Description

Batch gradient descent algorithm.The idea is to use all samples per iteration to update the parameters.

Usage

BGD(input_data, real_result, alpha, theta)

Arguments

input_data	Input_data matrix after adding constant 1 column
real_result	Real_result vector whose length is equal to the column number of data.
alpha	Learning rate
theta	The initial parameters of linear regression

Value

theta after iteration theta

Examples

## Not run: 
x <- seq(0.1,10,0.002)
n <- length(x)
y <- 2*x+5+rnorm(n)
z <- as.matrix(data.frame(rep(1,n),x))
theta <- BGD(z, y,0.002,c(1,1))
print(theta)

## End(Not run)

Sakoylf/StatComp21088 documentation built on Dec. 23, 2021, 10:22 p.m.