|
|
|
|
| LEADER |
03223nam a22005535i 4500 |
| 001 |
4809 |
| 003 |
DE-He213 |
| 005 |
20130725192920.0 |
| 007 |
cr nn 008mamaa |
| 008 |
100301s2009 xxu| s |||| 0|eng d |
| 020 |
# |
# |
|a 9780387886152
|9 978-0-387-88615-2
|
| 024 |
7 |
# |
|a 10.1007/978-0-387-88615-2
|2 doi
|
| 050 |
# |
4 |
|a QA402-402.37
|
| 050 |
# |
4 |
|a T57.6-57.97
|
| 072 |
# |
7 |
|a KJT
|2 bicssc
|
| 072 |
# |
7 |
|a KJM
|2 bicssc
|
| 072 |
# |
7 |
|a BUS049000
|2 bisacsh
|
| 072 |
# |
7 |
|a BUS042000
|2 bisacsh
|
| 082 |
0 |
4 |
|a 519.6
|2 23
|
| 100 |
1 |
# |
|a Mucherino, Antonio.
|e author.
|
| 245 |
1 |
0 |
|a Data Mining in Agriculture
|c by Antonio Mucherino, Petraq J. Papajorgji, Panos M. Pardalos.
|h [electronic resource] /
|
| 264 |
# |
1 |
|a New York, NY :
|b Springer New York,
|c 2009.
|
| 300 |
# |
# |
|a XVIII, 274p. 92 illus.
|b online resource.
|
| 336 |
# |
# |
|a text
|b txt
|2 rdacontent
|
| 337 |
# |
# |
|a computer
|b c
|2 rdamedia
|
| 338 |
# |
# |
|a online resource
|b cr
|2 rdacarrier
|
| 347 |
# |
# |
|a text file
|b PDF
|2 rda
|
| 490 |
1 |
# |
|a Springer Optimization and Its Applications,
|v 34
|x 1931-6828 ;
|
| 505 |
0 |
# |
|a Introduction to Data Mining -- 2 Statistical Methods -- 3 Clustering by k-means -- 4 k-nearest Neighbor Classification -- 5 Artificial Neural Networks -- 6 Support Vector Machines -- 7 Biclustering -- 8 Validation -- 9 An Application in C -- 10 Data Mining in a Parallel Environment -- 11 Solutions of the Exercises -- A. Matlab Environment -- B. C programming language -- C. Message Passing Interface (MPI) -- D. Eigenvalues and Eigenvectors -- References.
|
| 520 |
# |
# |
|a Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLABʼ. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ♭2009.
|
| 650 |
# |
0 |
|a Mathematics.
|
| 650 |
# |
0 |
|a Agriculture.
|
| 650 |
# |
0 |
|a Operations research.
|
| 650 |
# |
0 |
|a Environmental sciences.
|
| 650 |
1 |
4 |
|a Mathematics.
|
| 650 |
2 |
4 |
|a Operations Research, Mathematical Programming.
|
| 650 |
2 |
4 |
|a Math. Appl. in Environmental Science.
|
| 650 |
2 |
4 |
|a Mathematical Modeling and Industrial Mathematics.
|
| 650 |
2 |
4 |
|a Agriculture.
|
| 700 |
1 |
# |
|a Papajorgji, Petraq J.
|e author.
|
| 700 |
1 |
# |
|a Pardalos, Panos M.
|e author.
|
| 710 |
2 |
# |
|a SpringerLink (Online service)
|
| 773 |
0 |
# |
|t Springer eBooks
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9780387886145
|
| 830 |
# |
0 |
|a Springer Optimization and Its Applications,
|v 34
|x 1931-6828 ;
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-0-387-88615-2
|
| 912 |
# |
# |
|a ZDB-2-SMA
|
| 950 |
# |
# |
|a Mathematics and Statistics (Springer-11649)
|