jonpage/README.md

## README.md

      
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              README.md
            
          
    Clustering algorithms exist to assign observational units to relavant groups. A major problem is identifying the ideal number of groups if the true number is not known in advance.
This is the first in a series of blocks where we will create a visualization designed to help a domain expert identify the ideal number of groups for a set of time series observations.
The images above were created in R as part of the data analysis process. We'll use D3 to create an interactive version.
Next Step

  
## hdinc.png

      
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              hdinc.png
            
          
## index.html
<!DOCTYPE html>
<meta charset="utf-8">
<style>
img {
    display: block;
}
a {
    display: block;
}
</style>
<h2>Income from ages 25-65</h2>
<img src="hdinc.png" alt="Income Series"/>
<h2>Group Assignment with k = 10</h2>
<img src="kmeans_c_10.png" alt="Clusters for K = 10"/>
<a href="kmeans_matrix.pdf" target="_blank">Matrix of Clusters</a>

## kmeans_c_10.png

      
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              kmeans_c_10.png
            
          
## kmeans_matrix.pdf

      
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              kmeans_matrix.pdf
            
          
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## thumbnail.png

      
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              thumbnail.png
	<!DOCTYPE html>
	<meta charset="utf-8">
	<style>
	img {
	display: block;
	}
	a {
	display: block;
	}
	</style>
	<h2>Income from ages 25-65</h2>
	<img src="hdinc.png" alt="Income Series"/>
	<h2>Group Assignment with k = 10</h2>
	<img src="kmeans_c_10.png" alt="Clusters for K = 10"/>
	<a href="kmeans_matrix.pdf" target="_blank">Matrix of Clusters</a>