MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03840cam a22004098i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
22264078 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IN-BdCUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240516142155.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
210928s2022 enk d 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2021028230 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781032067049 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
LBSOR/DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
155.28 |
| Item number |
CEJ |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ceja, Enrique Garcia |
| Relator term |
Author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Behavior analysis with machine learning using R / |
| Statement of responsibility, etc. |
Enrique Garcia Ceja. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st Edition. |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
2112 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
London ; |
| -- |
Boca Raton : |
| Name of producer, publisher, distributor, manufacturer |
CRC Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2022. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxxiii, 397 p.; |
| Dimensions |
22 cm |
| Type of unit |
HB |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Chapman & Hall/CRC The R Series. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Introduction to behavior and machine learning -- Predicting behavior with classification models -- Predicting behavior with ensemble learning -- Exploring and visualizing behavioral data -- Preprocessing behavioral data -- Discovering behaviors with unsupervised learning -- Encoding behavioral data -- Predicting behavior with deep learning -- Multi-user validation -- Detecting abnormal behaviors. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data"-- |
| Assigning source |
Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Behavioral assessment |
| General subdivision |
Data processing. |
|
|---|
| Topical term or geographic name entry element |
Task analysis |
| General subdivision |
Data processing. |
|
|---|
| Topical term or geographic name entry element |
Machine learning. |
|
|---|
| Topical term or geographic name entry element |
R (Computer program language) |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Online version: |
| Main entry heading |
Garcia Ceja, Enrique. |
| Title |
Behavior analysis with machine learning using R. |
| Edition |
First edition |
| Place, publisher, and date of publication |
London ; Boca Raton : CRC Press, 2022 |
| International Standard Book Number |
9781003203469 |
| Record control number |
(DLC) 2021028231 |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
| Suppress in OPAC |
No |