117,69 €*
Versandkostenfrei per Post / DHL
Aktuell nicht verfügbar
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.
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.
Frank Acito is Professor emeritus, Indiana University, Bloomington
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
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xiii
314 S. 25 s/w Illustr. 130 farbige Illustr. 314 p. 155 illus. 130 illus. in color. |
ISBN-13: | 9783031456299 |
ISBN-10: | 3031456297 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Acito, Frank |
Auflage: | 1st ed. 2023 |
Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
Maße: | 241 x 160 x 24 mm |
Von/Mit: | Frank Acito |
Erscheinungsdatum: | 30.11.2023 |
Gewicht: | 0,658 kg |
Frank Acito is Professor emeritus, Indiana University, Bloomington
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
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xiii
314 S. 25 s/w Illustr. 130 farbige Illustr. 314 p. 155 illus. 130 illus. in color. |
ISBN-13: | 9783031456299 |
ISBN-10: | 3031456297 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Acito, Frank |
Auflage: | 1st ed. 2023 |
Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
Maße: | 241 x 160 x 24 mm |
Von/Mit: | Frank Acito |
Erscheinungsdatum: | 30.11.2023 |
Gewicht: | 0,658 kg |