Supervised machine learning for text analysis in R / (Record no. 125682)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01860cam a22003258i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 22083504 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260716150450.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210605s2022 flu b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780367554187 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780367554194 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.35 |
| Item number | HVI-S |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Hvitfeldt, Emil |
| 245 10 - TITLE STATEMENT | |
| Title | Supervised machine learning for text analysis in R / |
| Statement of responsibility, etc | Emil Hvitfeldt and Julia Silge |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Boca Raton : |
| Name of publisher, distributor, etc | CRC Press, |
| Date of publication, distribution, etc | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xix, 381 p. |
| 490 0# - SERIES STATEMENT | |
| Series statement | Data science series |
| 500 ## - GENERAL NOTE | |
| General note | Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing"-- Provided by publisher |
| 546 ## - LANGUAGE NOTE | |
| Language note | Eng |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational linguistics |
| General subdivision | Statistical methods. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Natural language processing (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Supervised learning (Machine learning) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Predictive analytics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Regression analysis. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Discriminant analysis. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | R (Computer program language) |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Silge, Julia |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Copy number |
|---|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2022-02-21 | 006.35 HVI-S | 141973 | 2025-03-03 | 2022-02-21 | Books | ||||
| UMT Main Campus | UMT Main Campus | 2026-07-16 | 006.35 HVI-S | 153369 | 2026-07-16 | 2026-07-16 | Books | C.2 |