Acito Predictive Analytics with KNIME

Analytics for Citizen Data Scientists
Erscheinungsjahr 2023
ISBN: 978-3-031-45630-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 314 Seiten, eBook

This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decision trees, and others) are covered with conceptual background as well as demonstrations of KNIME using each tool.The book uses KNIME, which is a comprehensive, open-source software tool for analytics that does not require coding but instead uses an intuitive drag-and-drop workflow to create a network of connected nodes on an interactive canvas. KNIME workflows provide graphic representations of each step taken in analyses, making the analyses self-documenting. The graphical documentation makes it easy to reproduce analyses, as well as to communicate methods and results to others. Integration with R is also available in KNIME, and several examples using R nodes in a KNIME workflow are demonstrated for special functions and tools not explicitly included in KNIME.

Zielgruppe

Graduate

Autoren/Hrsg.

Acito, Frank

Inhaltsverzeichnis

Chapter 1 Introduction to analytics.- Chapter 2 Problem definition.- Chapter 3 Introduction to KNIME.- Chapter 4 Data preparation.- Chapter 5 Dimensionality reduction and feature extraction.- Chapter 6 Ordinary least squares regression.- Chapter 7 Logistic regression.- Chapter 8 Decision and regression trees.- Chapter 9 Naïve Bayes.- Chapter 10 k nearest neighbors.- Chapter 11 Neural networks.- Chapter 12 Ensemble models.- Chapter 13 Cluster analysis.- Chapter 14 Communication and deployment

Über Autor(innen)

Frank Acito is Professor emeritus, Indiana University, Bloomington