easystats: Quickly investigate model performance

Quickly check all relevant assumptions for a linear regression model in one go. The check_model() function from #easystats #performance package does exactly this and also provides elegant visualizations with helpful pointers.

GET THE CODE SHOWN IN THE VIDEO:

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TABLE OF CONTENTS
00:00 Introduction to easystats performance
00:41 GitHub Project Setup
01:18 Libraries
01:49 Dataset: mpg
02:19 Model Performance
03:31 Exploring the Model Performance Plot
05:40 Tidymodels Integration
07:02 Learning More | R-Track Program

[perevales]

Great video, in fact, all videos of this series are fantastic. But I wonder if this package works on ML models, such as boosting. Thanks, Matt!!

[hneaz]

Are there any recommended packages like this to investigate multiple linear regression model or other models like random forest? Great video!

[HaiNguyen-sild]

Sir, may I ask a question?
When I use check_model() to check linearity in a logistic model, I get the result like:
"ERROR while rich displaying an object: Error: The viewport is too small to show this set of plots.
Please make it larger."
I use Jupyter Lab.
Thank you!

[CaribouDataScience]

What happened to the easystats package?

[waqaralikhan]

kindly guide how to incorporate the git in the rstudio just like you have done so that i can receive tips in my rstudio (or if you have a video or something kindly just link it)

[ruampimentel]

I've run your code, particulary this part:

`model_lm <- lm(hwy ~ displ + class, data = mpg)
model_lm
check_model(model_lm)
`

and I'm getting the following error:

`Error in grid.Call(C_convert, x, as.integer(whatfrom), as.integer(whatto), :
Viewport has zero dimension(s)`

Thoughts?

PS: I've installed all packages and dependencies.

[aallstar]

For some reason the video plays very fuzzy.