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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...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Päätekijä: Acito, Frank (Tekijä)
Yhteisötekijä: SpringerLink (Online service)
Aineistotyyppi: Elektroninen E-kirja
Kieli:englanti
Julkaistu: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Painos:1st ed. 2023.
Aiheet:
Statistics .
Data mining.
Statistics > Computer programs.
Statistics in Business, Management, Economics, Finance, Insurance.
Data Mining and Knowledge Discovery.
Statistical Software.
Linkit:https://doi.org/10.1007/978-3-031-45630-5
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Sisällysluettelo:
  • 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.

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