Machine Learning For Knowledge Discovery With R

Kao-Tai Tsai

Machine Learning For Knowledge Discovery With R - 1
Estado : Novo
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País de expedição : Reino Unido

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Machine Learning For Knowledge Discovery With R
Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs...

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Resumo

Machine Learning For Knowledge Discovery With R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs for data structure exploration, and result presentations. The book includes many real-world data examples from life-science, finance, etc. to illustrate the applications of the methods described therein.

Key Features:

  • Contains statistical theory for the most recent supervised and unsupervised machine learning methodologies.
  • Emphasizes broad statistical thinking, judgment, graphical methods, and collaboration with subject-matter-experts in analysis, interpretation, and presentations.
  • Written by statistical data analysis practitioner for practitioners.

The book is suitable for upper-level-undergraduate or graduate-level data analysis course. It also serves as a useful desk-reference for data analysts in scientific research or industrial applications.


Nº de Páginas: 264
Encadernação: Capa Dura / Hardback
Tema: Automatic control engineering
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Características

Número de páginas

264,0

Editora

Taylor & Francis

Peso

639,0

Data de lançamento

15/09/2021

Série/Edição Limitada

1

Idiomas

Inglês

EAN

9781032065366

Publicidade
Publicidade