Читайте только на ЛитРес

Книгу нельзя скачать файлом, но можно читать в нашем приложении или онлайн на сайте.

0+
текст
PDF

Объем 368 страниц

0+

Bayesian Networks. An Introduction

текст
PDF
Читайте только на ЛитРес

Книгу нельзя скачать файлом, но можно читать в нашем приложении или онлайн на сайте.

12 173,15 ₽
Подарите скидку 10%
Посоветуйте эту книгу и получите 1 217,32 ₽ с покупки её другом.

Авторы

О книге

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

Жанры и теги

Оставьте отзыв

Войдите, чтобы оценить книгу и оставить отзыв

Описание книги

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

Книга «Bayesian Networks. An Introduction» — читать онлайн на сайте. Оставляйте комментарии и отзывы, голосуйте за понравившиеся.
Возрастное ограничение:
0+
Дата выхода на Литрес:
03 июня 2018
Объем:
368 стр.
ISBN:
9780470684030
Общий размер:
4.2 МБ
Общее кол-во страниц:
368
Правообладатель:
John Wiley & Sons Limited