Textual Data Science with R by Mnica Bcuebertaut
Textual Statistics with Rcomprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.-
R Programming for Bioinformatics
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Music Data Analysis
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Bayesian Artificial Intelligence
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Visualization and Verbalization of Data
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Introduction to Data Technologies
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Combinatorial Inference in Geometric Data Analysis
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Time Series Clustering and Classification
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Correspondence Analysis and Data Coding with Java and R
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Semisupervised Learning for Computational Linguistics
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Pattern Recognition Algorithms for Data Mining
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Design and Modeling for Computer Experiments
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Microarray Image Analysis
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Data Science Foundations
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Modeling Data With Functional Programming in R
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Computational Statistics Handbook with MATLAB
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Bayesian Regression Modeling with INLA
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Exploratory Multivariate Analysis by Example Using R
"Even though textual data science cannot be considered as the youngest sibling of other data science fields, there is still quite a big space to be filled with up-to-date textbooks describing and analyzing various methods and facets of this very interesting topicIn this book, Mónica Bécue-Bertaut tries to fill this gap, giving theoretical and practical instructions about one of the relatively little known, but powerful methods in textual data science–Correspondence Analysis (CA)... Extensive graphical images and visualizations represented by various types of plot and diagram are used throughout the material, which provides an even better aid to the reader
for grasping the main ideas of the topic... separate mention should be drawn to the language used in the book. It is clear, simple, and even fun to read, providing an
understandable way of covering complex topics... Mónica Bécue-Bertaut achieved a good blend of theory and practice in her book, which can be used as a handy resource for students and beginners in data science, as well as for specialists in textual data analysis."
- Gia Jgarkava, ISCB December 2019
Mónica Bécue-Bertaut is an elected fellow of the International Statistical Institute and was named Chevalier des Palmes Académiques by the French Government. She taught statistics and data science at the Universitat Politènica de Catalunya and offered numerous guest lectures on textual data science in different countries. Dr. Bécue-Bertaut published several books (in French or Spanish) and work chapters (in English) on this last topic. She also participated in the design of software related to textual data science, such as SPAD.T and Xplortext; being this latter an R package.
| SKU | Unavailable |
| ISBN 13 | 9781032093659 |
| ISBN 10 | 103209365X |
| Title | Textual Data Science with R |
| Author | Mnica Bcuebertaut |
| Series | Chapman And Hall Crc Computer Science And Data Analysis |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2021-06-30 |
| Number of pages | 212 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |