國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

An introduction to machine learning

Kubat, Miroslav.

An introduction to machine learning

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An introduction to machine learningby Miroslav Kubat.
作者:	Kubat, Miroslav.
出版者:	Cham :Springer International Publishing :2015.
面頁冊數:	xiii, 291 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Machine learning.
電子資源:	http://dx.doi.org/10.1007/978-3-319-20010-1
ISBN:	9783319200101 (electronic bk.)

An introduction to machine learning
Kubat, Miroslav.

An introduction to machine learning[electronic resource] /by Miroslav Kubat. - Cham :Springer International Publishing :2015. - xiii, 291 p. :ill. (some col.), digital ;24 cm.

A Simple Machine-Learning Task -- Probabilities: Bayesian Classifiers -- Similarities: Nearest-Neighbor Classifiers -- Inter-Class Boundaries: Linear and Polynomial Classifiers -- Artificial Neural Networks -- Decision Trees -- Computational Learning Theory -- A Few Instructive Applications -- Induction of Voting Assemblies -- Some Practical Aspects to Know About -- Performance Evaluation -- Statistical Significance -- The Genetic Algorithm -- Reinforcement learning.

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of "boosting," how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.

ISBN: 9783319200101 (electronic bk.)

Standard No.: 10.1007/978-3-319-20010-1doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.3

An introduction to machine learning
LDR:02048nmm a2200325 a 4500 001 472553
003 DE-He213
005 20160223091622.0
006 m d
007 cr nn 008maaau
008 160316s2015 gw s 0 eng d
020 $a 9783319200101 (electronic bk.)
020 $a 9783319200095 (paper)
024 7 $a 10.1007/978-3-319-20010-1 $2 doi
035 $a 978-3-319-20010-1
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.3 $2 23
090 $a Q325.5 $b .K95 2015
100 1 $a Kubat, Miroslav. $3 727762
245 1 3 $a An introduction to machine learning $h [electronic resource] / $c by Miroslav Kubat.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xiii, 291 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a A Simple Machine-Learning Task -- Probabilities: Bayesian Classifiers -- Similarities: Nearest-Neighbor Classifiers -- Inter-Class Boundaries: Linear and Polynomial Classifiers -- Artificial Neural Networks -- Decision Trees -- Computational Learning Theory -- A Few Instructive Applications -- Induction of Voting Assemblies -- Some Practical Aspects to Know About -- Performance Evaluation -- Statistical Significance -- The Genetic Algorithm -- Reinforcement learning.
520 $a This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of "boosting," how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.
650 0 $a Machine learning. $3 188639
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Simulation and Modeling. $3 273719
650 2 4 $a Information Storage and Retrieval. $3 274190
650 2 4 $a Pattern Recognition. $3 273706
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-20010-1
950 $a Computer Science (Springer-11645)