Goal You will learn how to estimate the model performance with mlr3 using resampling techniques such as 5-fold cross-validation. Additionally, you will compare k-NN model against a logistic regression model. German Credit Data We work with the...

R-bloggers | R news and tutorials contributed by (750) R bloggers

25.04.2025

Train Predict Evaluate Basics | R-bloggers

Goal Our goal for this exercise sheet is to learn the basics of mlr3 for supervised learning by training a first simple model on training data and by evaluating its performance on hold-out/test data. German Credit Dataset The German credit dat...

R-bloggers | R news and tutorials contributed by (750) R bloggers

25.04.2025

Tree Methods | R-bloggers

Goal The goal for this exercise is to familiarize yourself with two very important machine learning methods, the decision tree and random forest. After this exercise, you should be able to train these models and extract important information to ...

R-bloggers | R news and tutorials contributed by (750) R bloggers

25.04.2025

Function Generators vs Partial Application in R | R-bloggers

In which I confront the way I read code in different languages, and end up wishing that R had a feature that it doesn’t. This is a bit of a thought-dump as I consider some code - please don’t take it as a criticism of any design choices; th...

home›R-bloggers | R news and tutorials contributed by (750) R bloggers

R-bloggers | R news and tutorials contributed by (750) R bloggers

Software

Resampling Solution | R-bloggers

Train Predict Evaluate Basics | R-bloggers

Tree Methods | R-bloggers

Function Generators vs Partial Application in R | R-bloggers

home
›
R-bloggers | R news and tutorials contributed by (750) R bloggers