Predictive Analytics with KNIME Analytics for Citizen Data Scientists /
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 u...
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| Yhteisötekijä: | |
| Aineistotyyppi: | Elektroninen E-kirja |
| Kieli: | englanti |
| Julkaistu: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
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| Painos: | 1st ed. 2023. |
| Aiheet: | |
| Linkit: | https://doi.org/10.1007/978-3-031-45630-5 |
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| Yhteenveto: | 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. |
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| Ulkoasu: | 1 online resource (XIII, 314 p. 155 illus.). 130 illus. in color. |
| ISBN: | 9783031456305 |
| DOI: | 10.1007/978-3-031-45630-5 |