Hierarchical Clustering - Revision history

Ed at 17:47, 21 September 2020

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Ed at 17:34, 21 September 2020

2020-09-21T17:34:32Z

Ed at 17:20, 20 September 2020

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Ed at 17:12, 20 September 2020

2020-09-20T17:12:14Z

Ed: /* Summary */

2019-05-29T19:20:05Z

Summary

Ed at 23:11, 27 May 2019

2019-05-27T23:11:47Z

Kyranstar: Created page with "{{McNair Projects |Has title=Hierarchical Clustering |Has owner=Kyran Adams, Oliver Chang, |Has start date=12/1/2017 |Has keywords=Cluster, Clustering, Circles, Pain in the as..."

2017-12-01T22:50:08Z

Created page with "{{McNair Projects |Has title=Hierarchical Clustering |Has owner=Kyran Adams, Oliver Chang, |Has start date=12/1/2017 |Has keywords=Cluster, Clustering, Circles, Pain in the as..."

New page

{{McNair Projects
|Has title=Hierarchical Clustering
|Has owner=Kyran Adams, Oliver Chang,
|Has start date=12/1/2017
|Has keywords=Cluster, Clustering, Circles, Pain in the ass, Agglomeration
|Has project status=Active
}}
Code located in <code>E:\McNair\Projects\FastCircles\src</code>.

This code takes a CoLevel master file, clusters points using k (number of clusters) in the range [1, num points / 5), and creates a file output.tsv.

Output.tsv has columns place, statecode, year, layer, cluster, lat, long, coname, datefirstinv. Layer is k, and cluster is the id of the cluster that the point belongs to.

You can run this program with:

<code>python3 main.py</code>

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 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=McNair Center
 |Has title=Hierarchical Clustering

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 {{Project
 |Has sponsor=McNair Center
 |Has title=Hierarchical Clustering

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 The code uses the AgglomerativeClustering from sklearn.cluster, which doesn't have GPU support.
 The input is a tdt file named CoLevelForCircles.txt with 7 columns:
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 The output is a tdt file named Results.tsv with 8 columns:
   (city, state, year) layer cluster ('lat','long','coname','datefirstinv')
 ==Documentation==

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 |Has project status=Active
 }}
-Code located in <code>E:\McNair\Projects\FastCircles\src</code>.
 This code takes a CoLevel master file, clusters points using k (number of clusters) in the range [1, num points / 5), and creates a file output.tsv.
 Output.tsv has columns place, statecode, year, layer, cluster, lat, long, coname, datefirstinv. Layer is k, and cluster is the id of the cluster that the point belongs to.
 You can run this program with:
 <code>python3 main.py</code>