An all inclusive guide to get well versed with Classifying and Clustering Data with R
About This Video
- Leverage the power of Data Analysis and Statistics using the R programming language.
- Discover best way to deal with temporal effects with time series analysis.
- Learn about the very intuitive and easy to explain features of Decision tree.
This video course provides the steps you need to carry out classification and clustering with R/RStudio software. You’ll understand hierarchical clustering, non-hierarchical clustering, density-based clustering, and clustering of tweets. It also provides steps to carry out classification using discriminant analysis and decision tree methods.
In addition, we cover time-series decomposition, forecasting, clustering, and classification. It includes several example sets of data that you can use for the methodologies covered. The approaches are illustrated using practical applications to data belonging to various fields.
By the end the course, you will be well-versed with clustering and classification using Cluster Analysis, Discriminant Analysis, Time-series Analysis, and decision trees.
Table of Contents
Chapter 1 : Cluster Analysis
- The Course Overview 00:02:29
- Iris Data 00:08:29
- Hierarchical Clustering Using Dendrogram with R 00:08:51
- Nonhierarchical K-means Clustering with R 00:11:17
- Preparing Data and Packages for Density-based Clustering 00:05:40
- Density-based Clustering with R 00:07:22
- Text Data Preparation for Clustering 00:07:00
- Clustering Words or Tweets with R 00:08:57
- Chapter 2 : Discriminant Analysis
- Chapter 3 : Time Series Analysis
- Chapter 4 : Decision Tree
- Title: Classifying and Clustering Data with R
- Release date: August 2017
- Publisher(s): Packt Publishing
- ISBN: 9781788294904