We have brought this eGuide focusing entirely on the concept of clustering using the FactoExtra Package of R programming language. But, Why clustering? Well, it is one of the most essential concepts of unsupervised machine learning that helps experts to draw references from datasets consisting of input data without labeled responses.
On the other hand, FactoExtra Package is known to provide easy to use functions for extracting or visualizing the multivariate data analysis output. It also includes CA, PCA, MCA, MFA & HMFA functions from different R packages.
This eGuide explains all the essential aspects of clustering and will give insights into the usage of different packages of R programming like Clustering or FactoExtra for data visualization.
This eGuide Includes:
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Intro to clustering
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Importance of clustering
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Types of clustering algorithms: Hierarchical clustering & Partitional clustering
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Installation of R packages like “Clustering” & “FactoExtra”
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Implementing the clustering procedure
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Descriptive statistics module & Scaling
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Implementing a Kmeans algorithm
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Visualizing the cluster plot
Learn the importance of clustering and the use of FactoExtra Package with this eGuide today!
