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| fixed length control field |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220610b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783030864415 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
121 |
| Item number |
PIE |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Pietsch, Wolfgang |
| 245 ## - TITLE STATEMENT |
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| Title |
On the epistemology of data science : conceptual tools for a new inductivism |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2022 |
| Place of publication, distribution, etc |
Cham : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xviii, 295 p. ; |
| Dimensions |
24 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
99.99 |
| Price type code |
EUR |
| Unit of pricing |
86.00 |
| 490 ## - SERIES STATEMENT |
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| Series statement |
Philosophical studies series |
| Volume number/sequential designation |
v.148 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
This book addresses controversies concerning the epistemological foundations of data science: Is it a genuine science? Or is data science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. Readers will discover a defense of inductivism and consideration of the arguments against it: an epistemology of data science more or less by definition has to be inductivist, given that data science starts with the data. As an alternative to enumerative approaches, the author endorses Federica Russo's recent call for a variational rationale in inductive methodology. Chapters then address some of the key concepts of an inductivist methodology including causation, probability and analogy, before outlining an inductivist framework. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of data science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in data science. Introductions to algorithms and brief case studies of successful data science such as machine translation are included. Data science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in data science. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Analogy |
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| Topical term or geographic name as entry element |
Bacon's tables |
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| Topical term or geographic name as entry element |
Determinism |
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| Topical term or geographic name as entry element |
Cusation |
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| Topical term or geographic name as entry element |
Causation |
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| Topical term or geographic name as entry element |
Decision trees |
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| Topical term or geographic name as entry element |
Experimentation |
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| Topical term or geographic name as entry element |
Gru problem |
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| Topical term or geographic name as entry element |
Indifference principle |
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| Topical term or geographic name as entry element |
K-means clustering |
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| Topical term or geographic name as entry element |
Ceteris Paribus laws |
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| Topical term or geographic name as entry element |
Mill's method |
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| Topical term or geographic name as entry element |
Non-redundancy principle |
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| Topical term or geographic name as entry element |
Overdetermination,causation |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Item type |
Books |