Gallery
In the gallery, you find case studies and demos. The posts are mostly about specific features and cover advanced topics. If you are completely new to mlr3 or machine learning, you should start with the book. Pick a post from one of the four categories or browse all posts sorted by date.
Latest
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Spatial Data in the mlr3 Ecosystem
Run a land cover classification of the city of Leipzig.
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Recursive Feature Elimination on the Sonar Data Set
Utilize the built-in feature importance of models.
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Shadow Variable Search on the Pima Indian Diabetes Data Set
Run a feature selection with permutated features.
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Default Hyperparameter Configuration
Run the default hyperparameter configuration of learners as a baseline.
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Hotstarting
Resume the training of learners.
Train and Evaluate Models
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Basic Machine Learning on Iris data set
Learn the basic operations train, predict, score, resample, and benchmark.
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Imbalanced Data Handling
Handle imbalanced data with oversampling, undersampling, and SMOTE imbalance correction.
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Resampling - Stratified, Blocked and Predefined
Apply stratified, block and custom resampling.
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Factor Encoding
Encode factor variables in a task.
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German Credit Series
Train, tune and pipeline different machine learning algorithms.
Optimize Models
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Hyperparameter Optimization on the Palmer Penguins Data Set
Optimize the hyperparameters of a classification tree with a few lines of code.
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Introduction to the mlr3tuningspaces Package
Apply predefined search spaces from scientific articles.
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Early Stopping with XGBoost
Simultaneously optimize hyperparameters and use early stopping.
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Recursive Feature Elimination on the Sonar Data Set
Utilize the built-in feature importance of models.
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Hyperband Series
Use the Hyperband optimizer with different budget parameters.
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Practical Tuning Series
Start with a tuned SVM and finish with a AutoML model.
Build Pipelines
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A Pipeline for the Titanic Data Set
Create new features and impute missing values with a pipeline.
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Pipelines, Selectors, Branches
Build a preprocessing pipeline with branching.
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Target Transformations via Pipelines
Transform the target variable.
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Tuning a Complex Graph
Tune a preprocessing pipeline and multiple tuners at once.
Apply Technical Tools and Run Special Tasks
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Production Example Using Plumber and Docker
Write a REST API using plumber and deploy it using Docker.
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Visualization in mlr3
Quickly plot objects of the mlr3 ecosystem.
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Spatial Data in the mlr3 Ecosystem
Run a land cover classification of the city of Leipzig.