Multivariate Statistics and Machine Learning in R For Beginners
With Applications in Biology and Medicine
Springer
ISBN 978-3-032-01850-2
Standardpreis
Bibliografische Daten
Fachbuch
Buch. Hardcover
2025
In englischer Sprache
Umfang: IV, 342 S.
Format (B x L): 15.5 x 23.5 cm
Verlag: Springer
ISBN: 978-3-032-01850-2
Produktbeschreibung
Each chapter links directly to videos, which explain the theoretical foundations of the statistical or machine learning methods in a basic way. Following each video, readers will find R code that replicates the analyses presented in the videos, empowering them to see real-world applications in action. Many exercises are included, allowing the readers to test their understanding of each concept through hands-on practice.
The book covers a comprehensive range of essential topics in multivariate statistics and machine learning, including fundamentals of matrix operations, multivariate plotting, and correlation, as well as methods for multivariate data analysis such as multivariate analysis of variance (MANOVA), principal component analysis (PCA), clustering, decision trees, discriminant analysis, random forest, partial least squares (PLS), canonical correlation analysis (CCA) and survival analysis. It also includes two case studies that reproduce the multivariate analyses in two scientific papers related to drug discovery and biomarker identification.
By integrating videos with practical coding examples, this text makes complex topics accessible for beginners. The interactive learning approach ensures that readers not only grasp the statistical theories and machine learning concepts but also gain the confidence to apply them effectively in real-world scenarios.
Autorinnen und Autoren
Produktsicherheit
Hersteller
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com