# Classification Practice

> ML preparation set.

- Stable ID: `classification-practice`
- Area: machine-learning
- Kind: practice
- Timebox: 40 minutes

Connect logistic probabilities and losses to threshold-dependent evaluation.

## Instructions

1. Distinguish probability estimation from the classification decision rule.

## Ordered items

1. [Logistic probability and cross-entropy](https://mlprep.iwase.dev/machine-learning/classification/original-ml-logistic/) — `original-ml-logistic` (6 min)
2. [Classification metrics from counts](https://mlprep.iwase.dev/machine-learning/classification/original-ml-metrics/) — `original-ml-metrics` (6 min)
3. [Logistic regression knowledge check](https://mlprep.iwase.dev/machine-learning/classification/google-mlcc-logistic-quiz/) — `google-mlcc-logistic-quiz` (10 min)
4. [Classification metrics knowledge check](https://mlprep.iwase.dev/machine-learning/classification/google-mlcc-classification-quiz/) — `google-mlcc-classification-quiz` (10 min)

## Completion

Compute a loss and evaluation metrics and explain threshold trade-offs.