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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: | 2024 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xiii
314 S. 25 s/w Illustr. 130 farbige Illustr. 314 p. 155 illus. 130 illus. in color. |
| ISBN-13: | 9783031456329 |
| ISBN-10: | 3031456327 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Acito, Frank |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 18 mm |
| Von/Mit: | Frank Acito |
| Erscheinungsdatum: | 30.11.2024 |
| Gewicht: | 0,499 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: | 2024 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xiii
314 S. 25 s/w Illustr. 130 farbige Illustr. 314 p. 155 illus. 130 illus. in color. |
| ISBN-13: | 9783031456329 |
| ISBN-10: | 3031456327 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Acito, Frank |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 18 mm |
| Von/Mit: | Frank Acito |
| Erscheinungsdatum: | 30.11.2024 |
| Gewicht: | 0,499 kg |
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