Linked Questions
20 questions linked to/from How to tell if data is "clustered" enough for clustering algorithms to produce meaningful results?
11
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usefulness of k-means clustering on high dimensional data [duplicate]
I wonder what is the usefulness of k-means clustering in high dimensional spaces, and why it can be better (or not) than other clustering methods when dealing with high dimensional spaces.
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0
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1
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Is there any way to know if my clusters are meaningful or meaningless? [duplicate]
Possible Duplicate:
How to tell if data is “clustered” enough for clustering algorithms to produce meaningful results?
I have used hierarchical clustering, e.g, Ward's method, single,...
- 21
0
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0
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14
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How do I choose k for k means clustering [duplicate]
Given a set of points, I'm trying to find the right cluster. However, I am lost on what the process is. Here is the graph of all possible points.
I am unsure what I should look at
whuang2017
145
votes
7
answers
114k
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Clustering on the output of t-SNE
I've got an application where it'd be handy to cluster a noisy dataset before looking for subgroup effects within the clusters. I first looked at PCA, but it takes ~30 components to get to 90% of the ...
- 12.8k
47
votes
4
answers
102k
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How to interpret mean of Silhouette plot?
Im trying to use silhouette plot to determine the number of cluster in my dataset. Given the dataset Train , i used the following matlab code
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- 4,337
59
votes
3
answers
40k
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How to select a clustering method? How to validate a cluster solution (to warrant the method choice)?
One of the biggest issue with cluster analysis is that we may happen to have to derive different conclusion when base on different clustering methods used (including different linkage methods in ...
- 909
10
votes
2
answers
8k
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R: update a graph dynamically [closed]
THis is a data visualization question. I have a database that contains some data that is constantly revised (online update).
What is the best way in R to update a graph every let say 5 or 10 seconds. (...
- 2,841
4
votes
2
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8k
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Use of bootstrap in clustering algorithms
Are there clustering algorithms that take advantage of bootstrap?
For example can one combine bootstrap with a standard K-Means algorithm to scale K-Means.
I was thinking if the following at a high-...
- 1,965
4
votes
1
answer
3k
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How can I assess how descriptive feature vectors are?
I am assessing how good different features are for unsupervised classification of a set of objects. For each different feature I test, I have computed a feature vector that describes the object. I ...
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4
votes
1
answer
3k
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Cubic clustering criterion in R [closed]
Does anybody know if any package calculates the cubic clustering criterion (CCC) index in R to aid the selection of optimal number of clusters?
- 3,632
5
votes
2
answers
2k
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Validate Cluster Analysis by doing it on two subsamples
I am working on validating a cluster analysis. I have read somewhere the approach to cross-validate the cluster analysis. The link of the article is
http://jonathantemplin.com/files/clustering/...
- 589
5
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2
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2k
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Calculating similarity and clustering question
I have a dataset of about a million companies containing their names, total employees and annual sales. I want to come up with a function that when given the company returns the 5 most similar ...
1
vote
4
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2k
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k-means clustering - Characterize clusters
I have a data set giving the number of visits for ~20 web pages for a total of ~3000 users. To indetify "similar" users according to the number of visits of each web page, I ran a k-means clustering.
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3
votes
1
answer
1k
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Which methods can help us to understand clustering model is good or bad?
In some clustering algorithm, ex: K-Means cluster, it is very sensitive with outliers, so we need to remove outliers before aplly ...
- 150
1
vote
1
answer
2k
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kMeans - acceptable value for WCSS
Which value for the within-cluster sum of squares points can be accepted regarding a data set of 1000 tuples, 21 attributes (but only 3 are used now)?
I have used Euclidean distance is used, and a ...
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