Classification reviews and checkpoint
Retrieve classification evidence across model families and complete the class-prediction checkpoint.
Helpful prior knowledge: Tune logistic regularisation · Validate k on a meaningful scale · Nonlinear SVM behaviour · One-R with numeric inputs · Classification trees · Match Naive Bayes to feature types · QDA allows class-specific shapes. These links are guidance, not locks.
Follow teaches the idea; Change asks you to make a choice; Transfer changes the context. Apply, reviews and checkpoints appear where the existing lessons provide them. Go Further lessons are optional.
Lessons in this model deck
Start with the first core lesson →
Classification evidence retrieval
Retrieve earlier concepts before combining them.
15–20 min · 3 practicesNeighbours, margins and rules retrieval
Retrieve earlier concepts before combining them.
15–20 min · 3 practicesTrees and distributions retrieval
Retrieve earlier concepts before combining them.
15–20 min · 3 practicesClassification checkpoint
Complete a stratified mixed Penguin logistic workflow with macro F1, a reference, tuning, a measurements-only ablation at the selected C on identical folds, and confusion evidence. Report the ablation fold scores in ablation_results and use them to qualify reliance on island/year/sex context.
25–35 min · 1 practicesBrowse all Classification lessons, reviews and checkpoints →