Feature\variable selection using RStudio

Hi everyone, hope you and your families are fine during this hard time.

Actually I have a big problem and really need help, I'm doing a project, and the aim is to apply feature\variable selection methods using R on some real data-set ( In this level only filter methods), I learnt R myself but I'm just a beginner, so I don't know how can I apply the data and how can I start writing codes or whatever the thing need. Moreover, my professor force me to finish filter methods during this month but I can't because I don't know!!
So please anyone can guide me or help me finding some resources or any kind of help.
thank you.

Hi, and welcome!

Please see the FAQ: What's a reproducible example (`reprex`) and how do I do one? Using a reprex, complete with representative data will attract quicker and more answers. We're not quite there yet, however. But keep in mind for coding related questions. Also, please review the homework policy for expectations on academic assignment related questions.

The first thing to do is to take a really deep diaphragm stretching breath. There's enough background stress in everyone's life that it's easy to get knocked off one's emotional balance with what seems like an impossible task. But you can do it.

The first thing is to describe the goal:

Using the XYZ dataset of [some set of variables], the goal is to select the [best][reasonable] variables and features to complete a [type of analysis] of the XYZ data set.

For example, strategies for variable selection are similar but quite distinct between ordinary least squares regression using lm and logistic regression, using glm.

So, the two questions are what data? and what model? And you can go from data to model or from model to data. Select the data and then the model that can take that type of data or select the model and find data that it will be able to handle.

I'm not entirely sure what filter methods that you have in mind. Does it involving selecting observations based on some set of criteria?

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