Cluster Analysis in R

R Tutorial 16.0

Cluster Analysis is a statistical technique for unsupervised learning, which works only with X variables (independent variables) and no Y variable (dependent variable).

We covered the topic in length and breadth in a series of SAS based articles (including video tutorials), let's now explore the same on R platform.

Forming cluster with categorical data

Most of people who know clustering might be aware about the back-end algorithm of the clustering(K-Means), provided the data is continuous.

Do you know how the clusters are being formed if the data is categorical?

Read the article to explore !

K-Means Clustering - Part 2 - Video Tutorial

Cluster Analysis - K-Means Clustering

Cluster Analysis is a technique of Unsupervised Learning in which objects (observations) similar to each other but distinct from other are marked in a group or Cluster. Cluster analysis is also called classification analysis. Cluster Analysis can be done by two methods : 1. Hierarchical Clustering and K-Means Clustering.
In this part we are covering SAS hands on session of second type of Cluster Analysis : K-Means Clustering.

K-Means Clustering - Part 1 - Video Tutorial

Cluster Analysis - K-Means Clustering

Cluster Analysis is a technique of Unsupervised Learning in which objects (observations) similar to each other but distinct from other are marked in a group or Cluster. Cluster analysis is also called classification analysis. Cluster Analysis can be done by two methods : 1. Hierarchical Clustering and K-Means Clustering.
In this part we are covering theory of second type of Cluster Analysis : K-Means Clustering.

Hierarchical Clustering - Part 2 - Video Tutorial

Cluster Analysis - Hierarchical Clustering

Cluster Analysis is a technique of Unsupervised Learning in which objects (observations) similar to each other but distinct from other are marked in a group or Cluster. Cluster analysis is also called classification analysis. Cluster Analysis can be done by two methods : 1. Hierarchical Clustering and K-Means Clustering.
In this part we are covering SAS hands on session of first type of Cluster Analysis : Hierarchical Clustering.

Hierarchical Clustering - Part 1 - Video Tutorial

Cluster Analysis - Hierarchical Clustering

Cluster Analysis is a technique of Unsupervised Learning in which objects (observations) similar to each other but distinct from other are marked in a group or Cluster. Cluster analysis is also called classification analysis. Cluster Analysis can be done by two methods : 1. Hierarchical Clustering and K-Means Clustering.
In this part we are covering theory of first type of Cluster Analysis : Hierarchical Clustering.

Cluster Analysis - Ready Reckoner

Cluster Analysis

It is a technique of Unsupervised Learning in which objects (observations) similiar to each other but distinct from other are marked in a group or Cluster. Cluster analysis is also called classification analysis.

In other words Cluster analysis means dividing the whole population into groups which are distinct among themselves but similar within.

Cluster Analysis can be done by two methods : 1. Hierarchical Clustering and K-Means Clustering.

Difference between K-Means and Hierarchical Clustering - Usage Optimization

When should I go for K-Means Clustering and when for Hierarchical Clustering ?

Often people get confused, which one of the two i.e. K-Means Clustering, and Hierarchical Clustering, techniques should be used for performing a Cluster Analysis.

Well, Answer is pretty simple, if your data is small then go for Hierarchical Clustering and if it is large then go for K-Means Clustering.

Why ???

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