What is Hierarchical Clustering?
Hierarchical Clustering is a technique to group objects based on distance or similarity. Hierarchical Clustering is often called as unsupervised learning because we let the machine (computer) learns mere from objects with their features and then the machine will automatically categorize those objects into groups. We do not specify which the objects suppose to be clustered into which group. In this hierarchical clustering tutorial, you will learn by numerical examples step by step on how to compute manually hierarchical clustering using agglomerative technique and validate the clustering using Cophenetic Correlation Coefficient in a very simple explanation.
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What you will get when you download it NOW?
In this Hierarchical Clustering Tutorial e-book you will learn, you will learn the following fascinating topics in a very SHORT TIME:
- What is Hierarchical Clustering?
- What is Dendogram?
- How Hierarchical Clustering Algorithm work?
- How to transform from Object Features to Distance Matrix?
- What is Linkages between Objects?
- Comprehensive step by step Numerical Example
- How to compute Cophenetic Correlation Coefficient?
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Only Companion File |
Complete Tutorial (Best Buy) |
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MS Excel Workbook on Hierarchical Clustering |
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Free 1 year update of companion files |
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Free 1 year update of Hierarchical Clustering Tutorial |
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Nice format of e-book of Hierarchical Clustering Tutorial in PDF format |
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