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Predictive analytics with KNIME = an...

Acito, Frank.

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Predictive analytics with KNIME = analytics for citizen data scientists /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predictive analytics with KNIME/ by Frank Acito.
其他題名:	analytics for citizen data scientists /
作者:	Acito, Frank.
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	xiii, 314 p. :illustrations (chiefly color), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Predictive analytics. -
電子資源:	https://doi.org/10.1007/978-3-031-45630-5
ISBN:	9783031456305

Predictive analytics with KNIME = analytics for citizen data scientists /
Acito, Frank.

Predictive analytics with KNIMEanalytics for citizen data scientists /[electronic resource] :by Frank Acito. - Cham :Springer Nature Switzerland :2023. - xiii, 314 p. :illustrations (chiefly color), digital ;24 cm.

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.

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.

ISBN: 9783031456305

Standard No.: 10.1007/978-3-031-45630-5doiSubjects--Uniform Titles:

KNIME (Computer file)
Subjects--Topical Terms:

3487786
Predictive analytics.

LC Class. No.: QA76.9.Q36

Dewey Class. No.: 001.42

Predictive analytics with KNIME = analytics for citizen data scientists /
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