Recent articles



Cluster Analysis in R Simplified and Enhanced




In R, standard clustering methods (partitioning and hierarchical clustering) can be computed using the R packages stats an...

DBSCAN: Density-Based Clustering Essentials




DBSCAN (Density-Based Spatial Clustering and Application with Noise), is a density-based clusering algorithm, introduced i...

Model Based Clustering Essentials




The traditional clustering methods, such as hierarchical clustering (Chapter @ref(agglomerative-clustering)) and k-means cl...

cmeans() R function: Compute Fuzzy clustering




This article describes how to compute the fuzzy clustering using the function cmeans() [in e1071 R package]. Previously, we...

Fuzzy C-Means Clustering Algorithm


In our previous article, we described the basic concept of fuzzy clustering and we showed how to compute fuzzy clustering....

Fuzzy Clustering Essentials




The fuzzy clustering is considered as soft clustering, in which each element has a probability of belonging to each cluster...

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Recent tutorials


ggpubr: Create Easily Publication Ready Plots




The ggpubr R package facilitates the creation of beautiful ggplot2-based graphs for researcher with non-advanced programmi...

The Ultimate Guide To Partitioning Clustering




In this first volume of symplyR, we are excited to share our Practical Guides to Partioning Clustering. The course materia...

Practical Guide to Principal Component Methods in R




Introduction Although there are several good books on principal component methods (PCMs) and related topics, we felt th...

Elegant correlation table using xtable R package




Correlation matrix analysis is an important method to find dependence between variables. Computing correlation matrix...

Saving High-Resolution ggplots: How to Preserve Semi-Transparency




This article describes solutions for preserving semi-transparency when saving a ggplot2-based graphs into a high quali...

F-Test: Compare Two Variances in R




F-test is used to assess whether the variances of two populations (A and B) are equal. Contents When to you u...

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Books on data science




Practical Guide to Principal Component Methods in R




This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large mu...[Read more]

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics




With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently....[Read more]

R Graphics Cookbook: Practical Recipes for Visualizing Data




This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb th...[Read more]

Hands-On Machine Learning with Scikit-Learn and TensorFlow




By using concrete examples, minimal theory, and two production-ready Python frameworks - scikit-learn and TensorFlow - author A...[Read more]

Practical Guide to Cluster Analysis in R




Although there are several good books on unsupervised machine learning, we felt that many of them are too theoretical. This book...[Read more]

R in Action: Data Analysis and Graphics with R




R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focus...[Read more]

An Introduction to Applied Multivariate Analysis with R




An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as m...[Read more]

Applied Predictive Modeling




Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocess...[Read more]

Practical Statistics for Data Scientists: 50 Essential Concepts




This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, an...[Read more]

R for Marketing Research and Analytics




This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical mod...[Read more]

R for Data Science




This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data sc...[Read more]

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