Classifying and Clustering Data with R [Video]

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Classifying and Clustering Data with R [Video]

Dr. Bharatendra Rai

An all inclusive guide to get well versed with Classifying and Clustering Data with R

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Video Details

ISBN 139781788294904
Course Length2 hours 29 minutes

Video Description

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.

Style and Approach

In depth content balanced with tutorials that put theory into practice. The Video course is a Practical tutorials to help you get beyond the basics of data analysis with R, using real-world data sets and examples.

Table of Contents

Cluster Analysis
The Course Overview
Iris Data
Hierarchical Clustering Using Dendrogram with R
Nonhierarchical K-means Clustering with R
Preparing Data and Packages for Density-based Clustering
Density-based Clustering with R
Text Data Preparation for Clustering
Clustering Words or Tweets with R
Discriminant Analysis
Discriminant Analysis with R
Model Interpretation
Visualization
Model Assessment
Time Series Analysis
Time Series Decomposition with R
Time Series Forecasting with R
Time Series Clustering with R
Time Series Classification with R
Decision Tree
Decision Tree with R
Visualization of Decision Trees
Prediction and Misclassification Errors

What You Will Learn

  • Know how to use hierarchical cluster analysis
  • Carry out cluster analysis using visualization methods such as Dendrogram and Silhouette plots
  • Find out how to perform non-hierarchical k-means clustering
  • See how to perform density-based clustering and clustering of tweets
  • Apply discriminant analysis for classification problems
  • Understand time-series decomposition, forecasting, clustering, and classification
  • Develop decision tree model for classification and prediction

Authors

Table of Contents

Cluster Analysis
The Course Overview
Iris Data
Hierarchical Clustering Using Dendrogram with R
Nonhierarchical K-means Clustering with R
Preparing Data and Packages for Density-based Clustering
Density-based Clustering with R
Text Data Preparation for Clustering
Clustering Words or Tweets with R
Discriminant Analysis
Discriminant Analysis with R
Model Interpretation
Visualization
Model Assessment
Time Series Analysis
Time Series Decomposition with R
Time Series Forecasting with R
Time Series Clustering with R
Time Series Classification with R
Decision Tree
Decision Tree with R
Visualization of Decision Trees
Prediction and Misclassification Errors

Video Details

ISBN 139781788294904
Course Length2 hours 29 minutes
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