Hierarchical clustering - Revision history

Sebastian at 15:22, 14 April 2020

2020-04-14T15:22:16Z

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	'''Hierarchical clustering''', also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref> Hierarchical clustering is often associated with heatmaps.<ref>[https://www.youtube.com/watch?v=7xHsRkOdVwo StatQuest: Hierarchical Clustering]youtube.com</ref>		'''Hierarchical clustering''', also known as hierarchical cluster analysis, is a [[clustering]] algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref> Hierarchical clustering is often associated with heatmaps.<ref>[https://www.youtube.com/watch?v=7xHsRkOdVwo StatQuest: Hierarchical Clustering]youtube.com</ref>

	== Strategies ==		== Strategies ==

Sebastian at 15:10, 14 April 2020

2020-04-14T15:10:52Z

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	Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:		Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:
	* Divisive: This type works on the assumption that all the feature vectors form a single set and then hierarchically go on dividing this group into different sets.<ref name="ssa">[https://www.sciencedirect.com/topics/computer-science/divisive-clustering Divisive Clustering]sciencedirect.com</ref>		* Divisive: This type works on the assumption that all the feature vectors form a single set and then hierarchically go on dividing this group into different sets.<ref name="ssa">[https://www.sciencedirect.com/topics/computer-science/divisive-clustering Divisive Clustering]sciencedirect.com</ref>
	* Agglomerative: In this type partitions are visualized using a tree structure called [[dendrogram]].<ref name="ssa"/>		* Agglomerative: The idea is to ensure nearby points end up in the same cluster.<ref>[https://www.youtube.com/watch?v=XJ3194AmH40 Agglomerative Clustering: how it works]youtube.com</ref> In this type, partitions are visualized using a tree structure called [[dendrogram]].<ref name="ssa"/>

	== Advantages vs disadvantages<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/h2iAD/more-on-hierarchical-clustering Hierarchical Clustering]Coursera</ref> ==		== Advantages vs disadvantages<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/h2iAD/more-on-hierarchical-clustering Hierarchical Clustering]Coursera</ref> ==

Sebastian at 14:30, 14 April 2020

2020-04-14T14:30:52Z

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	'''Hierarchical clustering''', also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref>		'''Hierarchical clustering''', also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref> Hierarchical clustering is often associated with heatmaps.<ref>[https://www.youtube.com/watch?v=7xHsRkOdVwo StatQuest: Hierarchical Clustering]youtube.com</ref>

	== Strategies ==		== Strategies ==

Sebastian at 14:28, 14 April 2020

2020-04-14T14:28:29Z

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	Hierarchical clustering, also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref>		'''Hierarchical clustering''', also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref>

	== Strategies ==		== Strategies ==
	Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:		Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:
	* Divisive:		* Divisive: This type works on the assumption that all the feature vectors form a single set and then hierarchically go on dividing this group into different sets.<ref name="ssa">[https://www.sciencedirect.com/topics/computer-science/divisive-clustering Divisive Clustering]sciencedirect.com</ref>
	* Agglomerative:		* Agglomerative: In this type partitions are visualized using a tree structure called [[dendrogram]].<ref name="ssa"/>

	== Advantages vs disadvantages<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/h2iAD/more-on-hierarchical-clustering Hierarchical Clustering]Coursera</ref> ==		== Advantages vs disadvantages<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/h2iAD/more-on-hierarchical-clustering Hierarchical Clustering]Coursera</ref> ==

Sebastian: /* Advantages vs disadvantagesHierarchical ClusteringCoursera */

2020-04-14T14:20:46Z

Advantages vs disadvantagesHierarchical ClusteringCoursera

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	* The hierarchical algorithm can never do any previous steps throughout the algorithm		* The hierarchical algorithm can never do any previous steps throughout the algorithm
	* The time complexity for the clustering can result in very long computation times in comparison with efficient algorithms such as [[K-means]].		* The time complexity for the clustering can result in very long computation times in comparison with efficient algorithms such as [[K-means]].
	* Tf we have a large data set, it can become difficult to determine the correct number of clusters by the dendrogram.		* If we have a large data set, it can become difficult to determine the correct number of clusters by the dendrogram.

	== References ==		== References ==

Sebastian at 01:34, 1 April 2020

2020-04-01T01:34:19Z

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	* It is easy to implement.		* It is easy to implement.
	* Hierarchical clustering produces a dendogram, which hlps with understanding the data.		* Hierarchical clustering produces a dendogram, which hlps with understanding the data.

			=== Disadvantages ===

			* The hierarchical algorithm can never do any previous steps throughout the algorithm
			* The time complexity for the clustering can result in very long computation times in comparison with efficient algorithms such as [[K-means]].
			* Tf we have a large data set, it can become difficult to determine the correct number of clusters by the dendrogram.

	== References ==		== References ==

Sebastian at 01:10, 1 April 2020

2020-04-01T01:10:39Z

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	* Divisive:		* Divisive:
	* Agglomerative:		* Agglomerative:

			== Advantages vs disadvantages<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/h2iAD/more-on-hierarchical-clustering Hierarchical Clustering]Coursera</ref> ==

			=== Advantages ===

			* Hierarchical clustering does not require the number of clusters to be specified.
			* It is easy to implement.
			* Hierarchical clustering produces a dendogram, which hlps with understanding the data.

	== References ==		== References ==

Sebastian at 00:02, 1 April 2020

2020-04-01T00:02:16Z

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			Hierarchical clustering, also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.<ref>[https://www.displayr.com/what-is-hierarchical-clustering/ What is Hierarchical Clustering?]displayr.com</ref>

	== Strategies ==		== Strategies ==
	Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:		Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:

Sebastian at 23:37, 31 March 2020

2020-03-31T23:37:55Z

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	* Divisive:		* Divisive:
	* Agglomerative:		* Agglomerative:

			== References ==

Sebastian: Created page with " == Strategies == Strategies for hierarchical clustering generally fall into two types[https://www.coursera.org/learn/machine-learning-with-python/lecture/cH..."

2020-03-31T23:37:34Z

Created page with " == Strategies == Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cH..."

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== Strategies ==
Strategies for hierarchical clustering generally fall into two types<ref name="intro">[https://www.coursera.org/learn/machine-learning-with-python/lecture/cHku3/intro-to-hierarchical-clustering Intro to Hierarchical Clustering]Coursera</ref>:
* Divisive:
* Agglomerative: