## 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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## 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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## 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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