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STHDA - EN : R data analysis
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R, statistics, data analysis, data visualization, plotting
R, statistics, data analysis, data visualization, plotting

359 followers
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STHDA - EN : R data analysis's posts

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Guide to Create Beautiful Graphics in R (Book, Edition 2)- Downloads
#rstats

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Factoextra R Package: Easy Multivariate Data Analyses and Elegant Visualization with #rstats

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ICYMI: My new book is out. Practical Guide to Cluster Analysis in R - #rstats

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(New book) Practical Guide to Cluster Analysis in R - #rstats http://buff.ly/2kHVfKg
++++++++++++++++++++
Although there are several good books on unsupervised machine learning/clustering and related topics, we felt that many of them are either too high-level, theoretical or too advanced. Our goal was to write a practical guide to cluster analysis, elegant visualization and interpretation.

The main parts of the book include:

- distance measures,
- partitioning clustering,
- hierarchical clustering,
- cluster validation methods, as well as,
- advanced clustering methods such as fuzzy clustering, density-based clustering and model-based clustering.

The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers.

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(New book) Practical Guide to Cluster Analysis in R - #rstats http://buff.ly/2kHVfKg
++++++++++++++++++++
Although there are several good books on unsupervised machine learning/clustering and related topics, we felt that many of them are either too high-level, theoretical or too advanced. Our goal was to write a practical guide to cluster analysis, elegant visualization and interpretation.

The main parts of the book include:

- distance measures,
- partitioning clustering,
- hierarchical clustering,
- cluster validation methods, as well as,
- advanced clustering methods such as fuzzy clustering, density-based clustering and model-based clustering.

The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers.

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Amazing articles from Marcin Kosiński showing how far one can customize survival curves using #rstats & #survminer

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Survival Analysis Toolkits - Easy Guides using #rstats http://buff.ly/2jdRzQT

In this document, we start by describing how to fit survival curves and how to perform logrank tests comparing the survival time of two or more groups of individuals. We continue by demonstrating how to assess simultaneously the impact of multiple risk factors on the survival time using the Cox regression model. Finally, we describe how to check the validy Cox model assumptions.

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Survival Analysis Toolkits - Easy Guides using #rstats http://buff.ly/2jdRzQT

In this document, we start by describing how to fit survival curves and how to perform logrank tests comparing the survival time of two or more groups of individuals. We continue by demonstrating how to assess simultaneously the impact of multiple risk factors on the survival time using the Cox regression model. Finally, we describe how to check the validy Cox model assumptions.

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Learn Methods to Evaluate the Validity of Cox Model Assumptions - Easy Guides using #rstats http://buff.ly/2iRNGmr
Survival analysis.
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