leaps | A pair programming service using operational transforms

For a course I'm attending, I have to perform a logistic stepwise regression to reduce the number of predictors of a feature to a fixed number and estimate the accuracy of the resulting model.

I've been trying with regsubsets() from the leaps package, but I can't get its accuracy.
Now I'm trying with caret, because I can set its metric to "Accuracy", but I can't fix the number of predictors when I use method = "glmStepAIC" in the train() function, because it has no tune parameters.

I am trying to get Github Action to check my package. The packages compiles fine (not even a note) on my computer. I created a yaml script to go into the github workflow directory using usethis::use_github_action_check_standard() but it fails with a bunch of warnings like

No files were found with the provided path: check. No artifacts will be uploaded.

The path check is a temporary directory created by rcmdcheck for storing files. So, I presume it is a problem connected with this command. But everything was created by the usethis utility and nobody else seems to have the same problem.

I looked around a lot and the last fix I tried was to manually add a step to install imported and suggested packages, as suggested in this post, to no avail.

What am I doing wrong? Thanks in advance.

the yaml script is

I'm using regsubsets from the leaps library to perform the best subset selection. I need to compare the coefficients it generates to the "true" coefficients I specified when simulating the data (by comparison, meaning, the difference between them squared, and the square root taken of the sum), for each number of predictors.

Since there are 16 different models that regsubsets generated, I use a loop to do this automatically. It would work except that when I extract the coefficients from the best model fit with x predictors, it only gives me the non-zero coefficients of the polynomial fit. This messes up the size of the coefi vector causing it to be smaller in size than the truecoef true coefficients vector.

If I could somehow force all coefficients to be spat out from the model, I wouldn't have an issue. But after looking extensively, I don't know how to do that.

Alternative ways of solving this problem would also be appreciated.

So I just discovered the very interesting Quake III inverse square root hack. After learning how it works and all, I decided to test it. I found that the hack only outperformed math.h 1/sqrt(X) when compiled with optimizations enabled.

The hack's implementation:

I've been using Selenium for some time to scrape a website but for some reasons it doesn't work anymore. I was using Selenium because you need to interact with the site to flip through pages (ie: click on a next button).

As a solution, I was thinking of using Post method from Requests. I'm not sure if its doable since I've never used the Post method, and since I not familiar with what it does (though I kind of understand the general idea).

My code would look something like that:

I am new to python and I'm building a web crawler to go through a list of articles on the internet and grab the text from them. When I use the function get_text(url), however, I am getting a lot of unnecessary text before and after the actual article content.

I do not know what to classify it as other than unnecessary (sorry for being vague). There is an example below.

Here is my code:

I was trying to shorten the process of passing the formula to the regsubsets() function instead of having to write the full string. So, I used the following code for generation of formula string but the regsubsets function gave the error "argument "y" is missing".

When I pasted the generated formula string without quotes, it was accepted. But when I pasted formula string within quotes, the same error was generated. So, it seems to me that, the quotes are the problem.

How can I bypass this error?
Is there another function that can pass a string argument without quotes to such picky functions?

Here's the code sample:

I have heard its a conventional practice to store program dependent files in /usr/share/application-folder in linux. So I'm trying to do it in my c program in a function called load_interface_files() for example. I am not sure if this is a good practice or not, I've heard about creating configuration files for this kind of issues.

Anyways, here's the the code I wrote to make a directory in /usr/share.

I would like to calculate the In-sample and Out-of-sample predictive accuracy for certain metrics, all while using carets' k-fold-cross validation.

So far I have got