عنوان

Pattern recognition and machine learning /

شابک

0387310738

شابک

9780387310732

شماره

dltt

عنوان اصلي

Pattern recognition and machine learning /

نام عام مواد

[Book]

نام نخستين پديدآور

Christopher M. Bishop

وضعيت ويراست

Corrected at 8th printing 2009

نام خاص و کميت اثر

xx, 738 pages :

ساير جزييات

illustrations (chiefly color) ;

ابعاد

24 cm

عنوان فروست

Information science and statistics

متن يادداشت

Textbook for graduates

متن يادداشت

Includes bibliographical references (pages 711-728) and index

متن يادداشت

Introduction. Example : polynomial curve fitting ; Probability theory ; Model selection ; The curse of dimensionality Decision theory ; Information theory -- Probability distributions. Binary vehicles ; Multinomial variables ; The Gaussian distribution ; The exponential family ; Nonparametric methods -- Linear models for regression. Linear basis function models ; The bias-variance decomposition ; Bayesian linear regression ; Bayesian model comparison ; The evidence approximation ; Limitations of fixed basis functions -- Linear models for classification. Discriminant functions ; Probabilistic generative models ; Probabilistic discrimitive models ; The Laplace approximation ; Bayesian logistic regression -- Neural networks. Feed-forward network functions ; Network training ; Error backpropagation ; The Hessian matrix ; Regularization in neural networks ; Mixture density networks ; Bayesian neural networks -- Kernel methods. Dual representations ; Constructing kernals ; Radial basis function networks ; Gaussian processes -- Sparse Kernel machines. Maximum margin classifiers ; Relevance vector machines -- Graphical models. Bayesian networks ; Conditional independence ; Markov random fields ; Inference in graphical models -- Mixture models and EM. K-means clustering ; Mixtures of Gaussians ; An alternative view of EM ; The EM algorithm in general -- Approximate inference. Variational inference ; Illustration : variational mixture of Gaussians ; Variational linear regression ; Exponential family distributions ; Local variational methods ; Variational logistic regression ; Expectation propagation -- Sampling methods. Basic sampling algorithms ; Markov chain Monte Carlo ; Gibbs sampling ; Slice sampling ; The hybrid Monte Carlo algorithm ; Estimating the partition function -- Continuous latent variables. Principal component analysis ; Probabilistic PCA ; Kernel PCA ; Nonlinear latent variable models -- Sequential data. Markoc models ; Hidden Markov models ; Linear dynamical systems -- Combining models. Bayesian model averaging ; Committees ; Boosting ; Tree-based models ; Conditional mixture models -- Data sets -- Probability distributions -- Properties of matrices -- Calculus of variations -- Lagrange multipliers

بدون عنوان

0

موضوع مستند نشده

Machine learning

موضوع مستند نشده

Pattern perception

موضوع مستند نشده

Pattern recognition systems

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Bishop, Christopher M.

تاريخ عمليات

20180313094141.0

قواعد فهرست نويسي ( بخش توصيفي )

rda

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y