Glossary · Phase 3 · Machine learning
Multiclass classification
Classification with more than two possible answers, such as sorting customers by their favorite product category.
Learn it properly
Multiclass classification · Softmax and cross-entropy for more than two classes. About 30 minutes.
Other terms from the same lesson
- confusion matrix: A table counting a classifier's predictions against the true answers: one row per true class, one column per predicted class. For yes/no it shows true and false positives and negatives.
- majority baseline: The accuracy you get by always predicting the most common class. A model has to beat it to be worth anything.
- softmax regression: Logistic regression for more than two classes: one score per class, turned into probabilities by softmax.