Update step_nearmiss.R

[PursuitOfDataScience]

Fixed a few typos.

Also, a quick question: does step_nearmiss() provide three different versions of near miss like this link? Thanks!

[EmilHvitfeldt]

Thank you for the PR!

This step only does what is called NearMiss-1 in that article. If you would like to see the other methods, feel free to add them in an issue so I can keep track, once I come around for more {themis} development

[PursuitOfDataScience]

Thank you.

I still have two questions: 1) When using step_nearmiss(), what if the model contains some nominal variables? Will the function tease them out automatically? 2) When comparing two plots from this link, they are essentially the same. I am wondering if step_tomek() really worked here?

[EmilHvitfeldt]

1. As per the documentation step_nearmiss() required

All columns used in this step must be numeric with no missing data.

so If there are nominal variables it will error.

2. It did work, it just doesn't remove too many points since that data is already fairly well separated. Highlighted are some points that were removed

[PursuitOfDataScience]

Thank you. The Tomek link is interesting. Based on the two plots shown, it seems like this method does not downsample the majority to the point where the classes are balanced. As you can see from the plot attached by you, there are still far more majority cases (Rest dots) than minority case (Circle dots). Could you help me understand this more? I am confused why the class ratio isn't 1 after using this method.

[PursuitOfDataScience]

Also, another follow-up question if you don't mind. Don't we just keep all the minority class observations and remove the majority class only? Why do these two points get removed at the same time?

[EmilHvitfeldt]

A tomek link is a pair of observations where they are different classes and nearest neighbors. This method then removes the whole link.

[EmilHvitfeldt]

The method could have been modified to only remove in the majority class, but right now it follows the literature (as far as I can tell)

[EmilHvitfeldt]

Tomek link removal is not as much about balancing, as it is removing "troublesome" observations

[EmilHvitfeldt]

If you find any particular documentation unclear please open an issue. :)

[PursuitOfDataScience]

Thanks for your clarification. When you check this link, you actually put step_tomek() under the category of "Under-sampling". When adding this step in the recipe, I doubt it will make a huge difference because two plots are very alike with only minor differences. I am wondering when this step will make the recipe perform better than the one without adding this step. I am very new to this method and it comes to be as a surprise to me that it doesn't work as I've thought.

[github-actions]

This pull request has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.