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== О чём писать ==
Объекты и признаки, классификация задач и подходов (с учителем и тд, классификация и тд), примеры задач
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Machine learning problems
• Supervised learning
• Unsupervised learning
• Semi-supervised learning
• Reinforcement learning
• Active learning
• Online learning
• Structured prediction
• Model selection and validation
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.
