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	<title>
	Comments on: Agglomerative Hierarchical Clustering	</title>
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	<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/</link>
	<description>Data Mining and Statistics for Decision Support</description>
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		<title>
		By: Zihao Liu		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-28970</link>

		<dc:creator><![CDATA[Zihao Liu]]></dc:creator>
		<pubDate>Sun, 12 Nov 2023 16:50:02 +0000</pubDate>
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					<description><![CDATA[Hi, I want to try the code on my computer. Do I need to go somewhere download the data set USArrests.csv?]]></description>
			<content:encoded><![CDATA[<p>Hi, I want to try the code on my computer. Do I need to go somewhere download the data set USArrests.csv?</p>
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		<item>
		<title>
		By: DAD		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-3924</link>

		<dc:creator><![CDATA[DAD]]></dc:creator>
		<pubDate>Tue, 17 Dec 2019 21:57:16 +0000</pubDate>
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					<description><![CDATA[Hey, thank you for your support. I wanted to color the labels based on the grouping they originally from and color the branches based on the new clustering. can you please help?]]></description>
			<content:encoded><![CDATA[<p>Hey, thank you for your support. I wanted to color the labels based on the grouping they originally from and color the branches based on the new clustering. can you please help?</p>
]]></content:encoded>
		
			</item>
		<item>
		<title>
		By: Jason		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2695</link>

		<dc:creator><![CDATA[Jason]]></dc:creator>
		<pubDate>Wed, 13 Nov 2019 03:23:12 +0000</pubDate>
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					<description><![CDATA[In reply to &lt;a href=&quot;https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2499&quot;&gt;Serkan Korkmaz&lt;/a&gt;.

The percentage is the variation of distance and it&#039;s in  2 dimensions. What you seeing is about 86% of the total distance between each point in each cluster, in a two dimension plot. If you add one more dimension it will increase]]></description>
			<content:encoded><![CDATA[<p>In reply to <a href="https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2499">Serkan Korkmaz</a>.</p>
<p>The percentage is the variation of distance and it&#8217;s in  2 dimensions. What you seeing is about 86% of the total distance between each point in each cluster, in a two dimension plot. If you add one more dimension it will increase</p>
]]></content:encoded>
		
			</item>
		<item>
		<title>
		By: Serkan Korkmaz		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2499</link>

		<dc:creator><![CDATA[Serkan Korkmaz]]></dc:creator>
		<pubDate>Sat, 19 Oct 2019 12:12:09 +0000</pubDate>
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					<description><![CDATA[Im not sure if I understand the output of the Scatterplot. We obviously have all the clusters, however, I cant seem to figure out what the percentages along the X and Y axis represents.

Are these the the fractions of the total variation in the data, that the clusters captures along each dimension?]]></description>
			<content:encoded><![CDATA[<p>Im not sure if I understand the output of the Scatterplot. We obviously have all the clusters, however, I cant seem to figure out what the percentages along the X and Y axis represents.</p>
<p>Are these the the fractions of the total variation in the data, that the clusters captures along each dimension?</p>
]]></content:encoded>
		
			</item>
		<item>
		<title>
		By: kassambara		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2184</link>

		<dc:creator><![CDATA[kassambara]]></dc:creator>
		<pubDate>Thu, 08 Aug 2019 06:42:27 +0000</pubDate>
		<guid isPermaLink="false">https://www.datanovia.com/en/?post_type=dt_lessons&#038;p=7687#comment-2184</guid>

					<description><![CDATA[In reply to &lt;a href=&quot;https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2182&quot;&gt;Jovana&lt;/a&gt;.

Thank you Jovana for this positive feedback, highly appreciated!]]></description>
			<content:encoded><![CDATA[<p>In reply to <a href="https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2182">Jovana</a>.</p>
<p>Thank you Jovana for this positive feedback, highly appreciated!</p>
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			</item>
		<item>
		<title>
		By: Jovana		</title>
		<link>https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/#comment-2182</link>

		<dc:creator><![CDATA[Jovana]]></dc:creator>
		<pubDate>Wed, 07 Aug 2019 12:58:38 +0000</pubDate>
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					<description><![CDATA[This article is amazing! It&#039;s simply, but skillfully written and easy to fallow. Can&#039;t wait to read new one!
P.S. I started loving my internship at bioinformatics lab even more now. Keep doing your mojo! :)]]></description>
			<content:encoded><![CDATA[<p>This article is amazing! It&#8217;s simply, but skillfully written and easy to fallow. Can&#8217;t wait to read new one!<br />
P.S. I started loving my internship at bioinformatics lab even more now. Keep doing your mojo! 🙂</p>
]]></content:encoded>
		
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