Logistic Regression in R

Logistic #regression is a simple, yet powerful #classification model. In this 12-minute tutorial, learn how to build a predictive classifier that classifies the age of a vehicle. Then use #ggplot to tell the story! Here are the links to get set up. 👇

Once you take these actions, you'll be set up to receive R-Tips with Code every week. 👍

THE R-TRACK PROGRAM
==============================
Learning R is tough, takes a long time, is advanced, is...

What am I say?! Learning R for business can be fast & fun. Here's how.

I have a complete system designed to teach you R, Data Science, Advanced Machine Learning, Web App Development, Time Series, & more - all for business. It's insanely powerful. Over 6+ months, learn everything needed to become an R Rockstar for Your Organization.

[wayarberry]

Excellent delivery. Just the right pace and the key points were clear. It sounds highly practiced! One of the things that seems to trip up a lot of you tube presentations is the presenter's fear of missing some obscure point and then later receiving criticism from a peer or "expert." They then launch into needless digressions which confuse the "zero day R person." This is an intro and you stuck to that mission. Great job.

[rohitekka]

This is a brilliant example of end to end logistic regression in R, out there.
Thanks!

[Sunny-China]

Very informative video. Sir, kindly make video on poisson regression and and how to calculate euclidean distance of sites. Thanks

[marcellberto]

Hey Matt,
Came across this gem of a tutorial, thanks for sharing! A couple of questions:
1) When evaluating the AUC, you used results_tbl %>% roc_auc(year, .pred_1999). Is there a reason why you didn’t use .pred_2008 instead?
2) In the feature importance chart, what do the numbers along the x-axis represent?
Your tutorials are great!

[ronjuahammad]

This tutorial is great! I wonder if it is possible to run logistic regressions for multiple response variables against several explanatory variables in a single coding? I would like to run logistic regressions for multiple outcomes (4 dependent variables) and 4-5 explanatory variables from the same dataset. The conventional approach is time consuming that runs individual logistic regressions (for each response variable) and summarise the outputs in a table.
Do you have any advise or tutorial please? Thank you.

[AdilKhan-shfv]

While splitting the train vs test, is it possible for the train set to contain excessive rows for a particular year, thus skewing the model? Is there a function to balance the #of year types I'm both, train n test sets?

[saikoushik]

where can I get mpg data shown in tutorial?

[aaskyboi]

I'm getting the following error when I enter the code for prediction_class_test :

Error in model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) :
factor fl has new levels c

[slprojecthub]

Is business science and data science are same?