Hypothesis Generation and Interpretation (Record no. 87221)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 04017nam a22006135i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-031-43540-9 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240730170842.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 231230s2024 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783031435409 |
-- | 978-3-031-43540-9 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 004.0151 |
100 1# - AUTHOR NAME | |
Author | Ishikawa, Hiroshi. |
245 10 - TITLE STATEMENT | |
Title | Hypothesis Generation and Interpretation |
Sub Title | Design Principles and Patterns for Big Data Applications / |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2024. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XII, 372 p. 177 illus., 125 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Big Data, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Basic Concept -- Hypothesis -- Science and Hypothesis -- Regression -- Machine Learning and Integrated Approach -- Hypothesis Generation by Difference -- Methods for Integrated Hypothesis Generation -- Interpretation. |
520 ## - SUMMARY, ETC. | |
Summary, etc | This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on "social infrastructure" applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-43540-9 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2024. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Database management. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data mining. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Machine learning. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Big data. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | System theory. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Theory of Computation. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Database Management. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data Mining and Knowledge Discovery. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Machine Learning. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Big Data. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Complex Systems. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2197-6511 ; |
912 ## - | |
-- | ZDB-2-SCS |
912 ## - | |
-- | ZDB-2-SXCS |
No items available.