=== Обучение с учителем (англ. ''Supervised learning'') ===
=== Обучение без учителя (англ. ''Unsupervised learning'') ===
=== Обучение с частичным привлечением учителя (англ. ''Semi-supervised learning'') ===
== Примеры задач ==
Supervised learning
A set of examples with answers is given. A
rule for giving answers for all possible
examples is required:
• classification;
• regression;
• learning to rank;
• forecasting.
Unsupervised learning
A set of examples without answers is given.
A rule for finding answers or some
regularity is required:
• clustering;
• association rules learning;
• recommender systems*;
• dimension reduction**.
How are the objects described?
f j ∶ X → D j , j = 1, ... , n are features or attributes.
Feature types:
• binary: D j = 0, 1 ;
• categorical: D j is finite;
• ordinal: D j is finite and ordered;
• numerical: D j = R.
== См. также ==
* [[Модель алгоритма и ее выбор]]
* [[Оценка качества в задаче кластеризации]]
* [[Кросс-валидация]]
== Примечания ==
