---
# System prepended metadata

title: Welcome to the R ladies Boook Club

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# Welcome to the R ladies Boook Club 
# "Hands-On Machine Learning with R" 
# Ch. 15. Stacked Models

## Some house rules to make the meeting nice for everyone

- Please familiarize with our [code of conduct](https://rladies.org/code-of-conduct/). In summary, please be nice to each other and help us make an **inclusive** meeting! :purple_heart: 
- The meeting will NOT BE RECORDED but the slides will be shared!
- Presenters are not necessarily topic experts :)
- Please list your name in the registry.
    - Make sure you're in the edit mode (ctrl + alt + e) when trying to edit the file! You'll know you're in the edit mode if the background is black :8ball:
- Please keep your mic off during the presentation. It is nice if you have the camera on and participate to make the meeting more interactive. Of course you can have your camera off if you prefer.
- If you have questions, raise your hand or write your question in this document.

### Links :link:

https://meet.jit.si/RLadiesBoookclubHOMLR15

Book/organisation:
- [Book: "Hands-On Machine Learning with R"](https://bradleyboehmke.github.io/HOML/)
- [GitHub Repository](https://github.com/rladiesnl/book_club_handsonML)
- [Meeting Link](https://us02web.zoom.us/j/89588323742#success)
- Meet-up pages:
    - [R-Ladies Utrecht](https://www.meetup.com/rladies-utrecht/)
    - [R-Ladies Den Bosch](https://www.meetup.com/rladies-den-bosch/)
- Twitter
    - [@RLadiesUtrecht](https://twitter.com/RLadiesUtrecht)
    - [@RLadiesDenBosch](https://twitter.com/RLadiesDenBosch)


## Chapter 15: Stacked Models

### Registry :clipboard: 
Name / pronouns / R level / place where you join from

- REGISTER HERE! :point_left: 
- Martine / advancedish / 's-Hertogenbosch NL
- Ece Ozler / she, her / intermediate / Rotterdam, NL
- Ale / she, her / intermediate / Utrecht NL
- Lill Eva / she, her / intermediate / Utrecht NL
- Gerbrich / she,er / intermediate / Utrecht NL 

### Do you have any questions? :question: 
You can write them down here, and if you have answers to posted questions please go ahead, we are all learning together.

- WRITE YOUR QUESTION HERE! :point_left: 


## About today's topic

### Any take-home messages you want to share?

Help others remember the main points you took of these chapters:

-  **Stacking models**: run multiple models individually in the same dataset and collect the predictions of all of them to create a super learner a.k.a. meta-model.
    -  The meta-model is trained again in the results of the other base learners
-  Steps:
    -  Choose the base learners that you want/need for your model
    -  Train the ensembl into each base learner using the exact same k-fold cross validation
    -  Predict on the new dataset (the predictions of the other models)
    -  Compare to the result of the individual learners
-  How to use the meta-model?
    -  Divide dataset in training (~80%) and test set (~20%)
    -  The training set is further divided again into a training-2 (75% of the training set)/test-2 (~25% of the training set). The base learners use the training-2 data to do 5 fold cross validation. Each base learner is tested in the test-2 dataset.
-  Function used `h20.stackedEnsembl()` (library `h20`)

### Do you have any interesting links regarding the topic? :link: 

If you have suggestions of books/blog posts/articles, etc. that could help people getting further into the topic. Write them here:

- WRITE YOUR LINK HERE! :point_left: 
- Tutorials from h20:  
 https://github.com/h2oai/h2o-tutorials
- Slidedecks rom h2o:  
https://github.com/h2oai/h2o-meetups

### Feedback :left_speech_bubble: 

Please help us get better at this by giving us some feedback :sparkles: Things you liked or things that could improve! :smile: 

- WRITE YOUR FIRST COMMENT HERE! :point_left:


## Sign-up for presenting a chapter!

- Chp 15 - Ece (20 Feb)
- Chp 16 - Brandon, co-author of the book (6 March)
- Chp 17 - Shweta (would try to) (20 March)
- Chp 18 - ?
- Chp 19 - ?
- Chp 20 - 21 -(22) - Martine (TBD)