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I was inspired by your pitch f/x videos to make several tidymodels versions. If interested, you can take a look here: https://github.com/datadavidz/pitch_fx
moneyball_part2 is the KNN/UMAP
moneyball_part3 is the Decision Tree/Random Forest
moneyball_part4 is the xgboost
moneyball_part5 is the Naive Bayes
Disclaimer: I am a novice at tidymodels.
I found the results similar/same as what you showed using caret or the native packages. I like the consistency in the tidymodels framework when switching across different models.
-Dave
The text was updated successfully, but these errors were encountered:
I was inspired by your pitch f/x videos to make several tidymodels versions. If interested, you can take a look here:
https://github.com/datadavidz/pitch_fx
moneyball_part2 is the KNN/UMAP
moneyball_part3 is the Decision Tree/Random Forest
moneyball_part4 is the xgboost
moneyball_part5 is the Naive Bayes
Disclaimer: I am a novice at tidymodels.
I found the results similar/same as what you showed using caret or the native packages. I like the consistency in the tidymodels framework when switching across different models.
-Dave
The text was updated successfully, but these errors were encountered: