Partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. Clustered-standard-errors and/or cluster-samples should be tagged as such; do not use the "clustering" tag for them.

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4
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4answers
1k views

Algorithm for choosing the number of clusters when using pam in R?

I am clustering a dataset using the pam command (from {cluster} package), and I wish to decide on the number of clusters to use. I was able to implement The_Elbow_Method in R (see wiki) for doing ...
20
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5answers
11k views

Clustering with a distance matrix

I have a (symmetric) matrix M that represents the distance between each pair of nodes. For example, A B C D E F G H I J K L A 0 20 ...
7
votes
1answer
723 views

Can someone explain the C-Index in the context of hierarchical clustering?

This is a followup to this question. I am currently trying to implement the C-Index in order to find a near-optimal number of clusters from a hierarchy of clusters. I do this by calculating the ...
21
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3answers
5k views

What stop-criteria for agglomerative hierarchical clustering are used in practice?

I have found extensive literature proposing all sorts of criteria (e.g. Glenn et al. 1985(pdf) and Jung et al. 2002(pdf)). However, most of these are not that easy to implement (at least from my ...
3
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3answers
3k views

Classification after factor analysis

I have analysed several dimensions in a survey. Each part of the survey represents a theoretical dimension and is analysed with factorial analysis. I want to use scores from factor analysis to do a ...
9
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5answers
3k views

Recommended books or articles as introduction to Cluster Analysis?

I'm working on a small (200M) corpus of text, which I want to explore with some cluster analysis. What books or articles on that subject would you recommend?
5
votes
1answer
246 views

Bias from increased information in FLAME clustering

I hope this is an appropriate forum for this question...if not, any pointers on a place to ask would be great. If my questions is not clear, please just let me know and I'll try to add ...
1
vote
1answer
135 views

For data similar to audio, how to determine if there are 1 or 2 categories? [closed]

I have to compare pairs of audio strems as 1d time series. Looking at the aligned trajectories I need to either cluster them together or assume they arise from independent generators. I remember ...
7
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2answers
2k views

Newman's modularity clustering for graphs

I am interested in running Newman's modularity clustering algorithm on a large graph. If you can point me to a library (or R package, etc) that implements it I would be most grateful. best ~lara
14
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8answers
4k views

Visualization software for clustering

I want to cluster ~22000 points. Many clustering algorithms work better with higher quality initial guesses. What tools exist that can give me a good idea of the rough shape of the data? I do want to ...
1
vote
1answer
97 views

How to identify points and an unknown distribution in a two type clustering problem?

I have a data set that contains two types of points. The first type of points come from an N(0,1) distribution. The second type of points come from an N(m,v) distribution for some real m and some ...
8
votes
3answers
2k views

How can I test whether my clustering of binary data is significant

I'm doing shopping cart analyses my dataset is set of transaction vectors, with the items the products being bought. When applying k-means on the transactions, I will always get some result. A random ...
6
votes
4answers
576 views

Working through a clustering problem

Say I've got a program that monitors a news feed and as I'm monitoring it I'd like to discover when a bunch of stories come out with a particular keyword in the title. Ideally I want to know when ...
7
votes
3answers
141 views

How to deal with the effect of the order of observations in a non hierarchical cluster analysis?

When a non-hierarchical cluster analysis is carried out, the order of observations in the data file determine the clustering results, especially if the data set is small (i.e, 5000 observations). To ...
3
votes
4answers
946 views

What tools could be used for applying clustering algorithms on MovieLens?

I need to analyze the 100k MovieLens dataset for clustering with two algorithms of my choice, between the likes of k-means, agnes, diana, dbscan, and several others. What tools (like Rattle, or Weka) ...
7
votes
4answers
335 views

Clustering of large, heavy-tailed dataset

I have a dataset of 130k internet users characterized by 4 variables describing users' number of sessions, locations visited, avg data download and session time aggregated from four months of ...