Introduction to machine learning
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Read More ↓Title Statements
- Full title :Introduction to machine learning / Ethem Alpaydin.
Summary
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Read More ↓Edition Statements
- Publication Date:©2014
- Edition:Third edition
Publication Statements
- Publisher(s):The MIT Press
- Place of Publication:Cambridge, MA
- Language:eng
- Publication Date:©2014
The Physical Object
- Description:XXII, 613 pagina's : : illustraties ; : 24 cm.
Edition Identifiers
- ISBN:0262028182, 9780262028189
- oclc:ocn921497092
- LC Classification:Q325.5
- Dewey Decimal:006.3/1
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