faridcher / ml-course Goto Github PK

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.

Hi Fared,
The 94th line of the ex3_nn.R reads as follows:
pred <- predict(Theta1, Theta2, X[rp[i],])

It is called from inside this loop:
for (i in 1:m){
pred <- predict(Theta1, Theta2, X[rp[i],])
}

I am getting the following error:

pred <- predict(Theta1, Theta2, X[rp[1],])
Error in rep(0, m) : invalid 'times' argument

The predict function worked fine when it was invoked the first time in the same program at line 76
pred <- predict(Theta1, Theta2, X)

I could not find anything wrong with the repeat command used inside the predict function at row 14
p <- rep(0,m) where m <- dim(X)[1]

I am not sure if the function results are cached in R the first time which causes problem when called again.

Can you please help.

https://github.com/faridcher/machine-learning-course/blob/master/Solutions/mlclass-ex3/ex3_nn.R

All images in the wiki appear to be broken. E.g. https://github.com/faridcher/ml-course/wiki/instructions#21-plotting-the-data under "Figure 1: Scatter plot of training data" all I see is a broken image link icon.

Was getting a strange error in assignment 3. Turns out the sigmoid function in sigmoid.R is blank, but there is no * indicaated that it needs to be completed in the Introduction to the assignment https://github.com/faridcher/ml-course/wiki/3#introduction

While submitting, i receive this error !! Submission failed: unexpected error: object 'grad' not found
!! Please try again later.Error: object of type 'special' is not subsettable

Please help me!

Hi Fared,
Curios to know why you create function within function (Theta as a subfunction of cost function).
For example,

linearRegCostFunction <- function(X, y, lambda) {
function(theta) {

why not
linearRegCostFunction <- function(X, y, lambda,theta) {

Is it just a coding style or there is a particular reason.

Thanks in advance.

Hi
First things first, thank you for this very good resource for leaarning maching learning. May the good lord continue to bless you.

However I have an error in running ex1.R.
I keep getting this error message below

Running warmUpExercise ...
5x5 Identity Matrix:
Error in warmUpExercise() : object 'A' not found

Any help.
Thanks

P.S I have tried this also.. same result

source("D:/UIUC PHD/MACHINE LEARNING/COURSERA/EXERCISES/1/ex1.R")
Running warmUpExercise ...
5x5 Identity Matrix:
Error in warmUpExercise() : object 'A' not found

Hi, I've been having a problem with submission (please see below).

Do you have any idea why this might be happening?

Cheers
Bob

source("submit.r")
submit()
== Submitting solutions | Linear Regression with Multiple Variables...
Login (email address):
[email protected]
token:
4BIEsjivD1WGjERU
!! 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

E.g. the latex in https://github.com/faridcher/ml-course/wiki/3#131-vectorizing-the-cost-function

Thank you so much for creating this repository. This is exactly what I need! I am very eager to get this up and running, however, in testing it out, when trying to submit the warm up exercise in exercise 1, I get the following error message:

!! Submission failed: unexpected error: object 'A' not found
!! Please try again later.Error: object of type 'special' is not subsettable

This error occurs after entering my coursera email and the token.

Attached is the exact code which I run to produce the error, and below is some info regarding my R version and ubuntu system:

Any help on this issue would be great.
Thanks again!

R.Version()
$platform
[1] "x86_64-pc-linux-gnu"

$arch
[1] "x86_64"

$os
[1] "linux-gnu"

$system
[1] "x86_64, linux-gnu"

$status
[1] ""

$major
[1] "3"

$minor
[1] "4.2"

$year
[1] "2017"

$month
[1] "09"

$day
[1] "28"

$svn rev
[1] "73368"

$language
[1] "R"

$version.string
[1] "R version 3.4.2 (2017-09-28)"

$nickname
[1] "Short Summer"

submission problem warm up.txt

Hello Farid,
I am a newbie in R; finding your Github repository very useful in coming up to speed.

Can you please help me understand how you converted a matlab file (.mat) into an R file (.Rda)

https://github.com/faridcher/ machine-learning-course/tree/ master/Starter/mlclass-ex3

from ex3data1.mat in matlab to
'ex3data1.Rda'

Thank you for the help.