Общие понятия
WARNING
СТАТЬЯ В АКТИВНОЙ РАЗРАБОТКЕ
О чём писать
Объекты и признаки, классификация задач и подходов (с учителем и тд, классификация и тд), примеры задач
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.
