The following is the original code from your starter section
gradientDescentMulti <- function(X, y, theta, alpha, num_iters) {
#GRADIENTDESCENTMULTI Performs gradient descent to learn theta
# theta <- GRADIENTDESCENTMULTI(x, y, theta, alpha, num_iters) updates theta by
# taking num_iters gradient steps with learning rate alpha
# Initialize some useful values
m <- length(y) # number of training examples
J_history <- rep(0,num_iters)
for (iter in 1:num_iters) {
# ---------------------- YOUR CODE HERE ----------------------
# Instructions: Perform a single gradient step on the parameter vector
# theta.
#
# Hint: While debugging, it can be useful to print out the values
# of the cost function (computeCostMulti) and gradient here.
#
}
# ------------------------------------------------------------
# Save the cost J in every iteration
J_history[iter] <- computeCostMulti(X, y, theta)
}
list(theta = theta, J_history = J_history)
}
We get following error
> submit()
== Submitting solutions | Linear Regression with Multiple Variables...
Login (email address):
username(#replaced)
token:
token(#replaced)
!! Submission failed: unexpected error: gradientDescentMulti.R:29:1: unexpected '}'
28: list(theta = theta, J_history = J_history)
29: }
^
!! Please try again later.
Error in response$errorMessage :
object of type 'special' is not subsettable
The curly brace above save the cost J in every iteration should be commented out. The issue pointed by one of the user might be because of this. After commenting that curly brace, the program is working fine. Thanks for developing this and making available for free.
The following is the original code from your starter section
We get following error
The curly brace above
save the cost J in every iteration
should be commented out. The issue pointed by one of the user might be because of this. After commenting that curly brace, the program is working fine. Thanks for developing this and making available for free.