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Improve imblaearn exercise: also show the effect of weighting

Status: Open.

#49 In slds-lmu/lecture_appml;

· mfeurer opened on Jun 18, 2025

Improve Calibration Homework Python

Status: Open.

#48 In slds-lmu/lecture_appml;

· mfeurer opened on Jun 18, 2025

Simplify exercise

Status: Open.

#47 In slds-lmu/lecture_appml;

· mfeurer opened on Jun 4, 2025

Replace credit-g or use other loss function

Status: Open.

#46 In slds-lmu/lecture_appml;

· mfeurer opened on May 30, 2025

Use same seed for random search when comparing pipelines and only tuning the machine learning algorithm

Status: Open.

#45 In slds-lmu/lecture_appml;

· mfeurer opened on May 30, 2025

Target Encoding: mention embeddings in neural networks

Status: Open.

#44 In slds-lmu/lecture_appml;

· mfeurer opened on May 28, 2025

Boruta (feature selection): nice example

Status: Open.

#43 In slds-lmu/lecture_appml;

· mfeurer opened on May 27, 2025

Categorical Encoding: Add CatBoost example

Status: Open.

#42 In slds-lmu/lecture_appml;

· mfeurer opened on May 27, 2025

python exercise [03_1_encoding]: mlr3 xgboost support for categorical data?

Status: Open.

#39 In slds-lmu/lecture_appml;

· sandylaker opened on May 20, 2025

Add Exercise on incorrect preprocessing

Status: Open.

#38 In slds-lmu/lecture_appml;

· mfeurer opened on May 20, 2025

python exercise [03_2_xgboost]: Use brier score instead of ACC for imbalanced dataset

Status: Open.

#36 In slds-lmu/lecture_appml;

· sandylaker opened on May 17, 2025

Python exercise [03_1_encoding_scaling]: xgboost python is about to support categorical data while R hasn't yet.

Status: Open.

#35 In slds-lmu/lecture_appml;

· sandylaker opened on May 17, 2025