Cluster analysis is the task of 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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Compute probability of a grouping being correct

I have an exemplar grouping of objects (each with their own feature vector) into categories. I am then given a new grouping of compeltely different objects, and Iw would like to compute the ...
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2answers
9k views

Determine different clusters of 1d data from database

I have a database table of data transfers between different nodes. This is a huge database (with nearly 40 million transfers). One of the attributes is the number of bytes (nbytes) transfers which ...
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3answers
156 views

How can I separate each of 100 observations into groups as determined by the data?

I have 3 covariates for 100 observations. How can I separate each of my 100 observations into groups as determined by the data. I was thinking clustering. However, apparently, I need more than 3 ...
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5answers
886 views

Does preclustering help to build a better predictive model?

For the task of churn modelling I was considering: Compute k clusters for the data Build k models for each cluster individually. The rationale for that is,that there is nothing to prove, that the ...
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2answers
135 views

Is concept of similarity objective?

Imagine following example: We have two pairs of points (i.e. 4 objects in some space) and two similarity measures. According to first similarity measure, objects from first pair are more similar then ...
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1answer
348 views

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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1answer
146 views

Distance independent approximation of Nearest Neighbor/k-NN.

Nearest neighbor/k-NN for use with Normalized Compression Distance. I wonder if there exist any approximation of NN/k-NN algorithm which work for all distance measures ? I would like to test ...
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1answer
995 views

Clustering of time series

I have a set of almost 1600 time series on 2 years which I want to group into clusters. Do you think this is possible using k-means? Which method do you advice me to use? Is this possible at all using ...
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2answers
901 views

Image Clustering with K-means - Postprocessing

I did some clustering on an image (each pixel is an observation that has 5 variables associated with it), I get pretty detailed results but they are a little bit noisey... I think. I used K-means. ...
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4answers
640 views

How to measure shape of cluster?

I know that this question is not well defined, but some clusters tend to be elliptical or lie in lower dimensional space whilst the other have nonlinear shapes (in 2D or 3D examples). Is there any ...
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3answers
3k views

How to reduce the number of variables in cluster analysis?

I've got 10 (yes, only 10) cases over 1000 variables (e.g. measurements of concentrations of 1000 different compounds at 10 different time points). I can group these cases into 3 clusters in ...
3
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1answer
4k views

What to use, k-means or hierarchical clustering for presence absence data?

I am currently working with a presence-absence database that is mostly zeros (~5% are ones) representing species in space (a species per site matrix). I would like to explore the spatial pattern of ...
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1answer
728 views

Which are the most effective clustering ensembles?

In supervised learning, there are some ensemble methods that overcome others significantly (adaboost or random forests to mention some). Few years later, also ensembles in unsupervised learning were ...
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153 views

Seeking for a fast non parametic clustering algorithm

I'm looking for a fast clustering method to cluster a large kind of datas to a unknown count of clusters. I know about the PAM-Algorithm. But it's only efficient for low datasets. Is there a ...
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2answers
1k views

Clustering time series with wavelets in R

Can discrete wavelet trasform be used for feature extraction from time series in order to cluster them? Any R code how to do this will be appreciated.
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2answers
246 views

What function of distance for the questionnaire data?

I have data from questionnaire from school. First question is study program (only 2 programs) and next 35 questions are various questions (influence of friends etc.) Possible answers for 35 questions ...
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1answer
575 views

An incremental Gaussian mixture model

Question 1: Suppose that data is modelled by a mixture of K probability distributions which are actually Gaussians. $P(x_i|\theta_j)$ is the probability density of the j'th cluster, for which the ...
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0answers
62 views

How to sum cluster data?

I have a binary variable with probit model, i.e., $P(Y_{ij}=1|X_j)= \Phi(a_i+b_iX_j)$, where $X_j$ is $\mathcal N(0,1)$, and $a_i$ and $b_i$ are regression parameters. I am wondering what the ...
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2answers
601 views

Interpret Silhouette plot for large microarray dataset

For a microarray experiment with ~40,000 probes and ~30 samples I used the clara function from R to cluster my expression matrix. How do I interpret this silhouette plot? Firstly, I don't ...
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2answers
323 views

What are features that distinguish clustering, blind signal separation and dimensionality reduction?

In terms of input -> [process] -> output what are features that distinguish clustering, blind signal separation and dimensionality reduction? From this ...
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3answers
529 views

Metric and Clustering Method

I need some suggestions regarding what kind of metric and clustering analysis I should use. I read a lot of posts but didn't get any hints about this type of data. I have a 3000*5000 matrix, where ...
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0answers
344 views

Clusters produced by R intersect

I am new here - and relatively new to statistics, data mining and R. I am trying to understand why my data is not clustering correctly - or if I am reading it wrong. Shortly about the project: My ...
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2answers
363 views

Organizing cluster analysis results in a database

I'm a newbie in cluster analysis so please excuse me if my question seems to be very basic. I'm using SPSS and Matlab for performing cluster analysis in a variety of datasets. Dendograms are great for ...
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3answers
286 views

Clustering algorithm and distance function for sets

I am willing to run a clustering algorithm on data records consisting in sets each one representing the features enabled at a certain time. Is there any clustering algorithm you would recommend me to ...
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2answers
3k views

Good clustering Java library

I'm looking for a good Java library implementing several clustering algorithms. I'll have to cluster some programs execution traces and I still don't know which algorithms I am going to need, so I'd ...
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1answer
668 views

Are Bayesian approches used for classification (supervised) or for clustering (unsupervised)?

Are Bayesian approaches (static and dynamic) used for classification (which is supervised) or for clustering (which is unsupervised)? or can they be used for both ? I even see that for instance to ...
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4answers
4k views

Singular covariance matrix in Mahalanobis distance in Matlab

I am using the Mahalanobis distance to classify an unknown 64-dimensional vector into one of 75 classes. There are n samples of 64-dimensional vectors for each class, arranged into an Nx64 matrix ...
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3answers
11k views

Supervised clustering or classification?

The second question is that I found in a discussion somewhere on the web talking about "supervised clustering", as far as I know, clustering is unsupervised, so what is exactly the meaning behind ...
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2answers
65 views

Clustering based on interactions between members of two groups

I have a large dataset from a survey that describes what web pages people use. So for each person I have a list of pages that they visit and how frequently they visit them. What methods can be used to ...
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3answers
491 views

Can unsupervised evaluation measures for clustering replace a supervised evaluation measure?

Is it possible to have the same evaluation performances when comparing some clustering algorithms using many unsupervised evaluation measures instead of a supervised one ?
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2answers
508 views

Evaluating clusters of first-order Markov chains

I clustered my dataset of several thousand first-order Markov chains into about 10 clusters. Is there some recommended way how I can evaluate these clusters and find out what the items in the ...
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2answers
650 views

Finding most informative feature subsets given dataset, clustering algorithm and gold standard partition

I have an $n \times m$ matrix of data $\mathbf{D}$ as well as a $k$-partition $P$ of $n$ indices each representing a row in $\mathbf{D}$. Assuming an arbitrary clustering algorithm $A$, I would like ...
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1answer
235 views

How to compute distances within & between clusters, if clusters contain sequences?

I applied number of methods of clustering, and I want to evaluate these different methods using Dunn index, in this method I have to calculate the distance among clusters and among points in clusters. ...
2
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1answer
128 views

Document image analysis and retrieval with online incremental clustering

Is there any interesting problem in the area of "Document Image Analysis and Retrieval" which by nature needs an online/incremental clustering process ? The problem may be in the context of "Logical ...
0
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1answer
146 views

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, ...
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1answer
295 views

Data reduction of 3D points

[This is my first post to CrossValidated, I hope I'm not off-topic] I have data consisting of ~10^6 points in 3D space. We want to try out some surface fitting algorithms that cannot handle this high ...
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1answer
212 views

Finding “weak ties” in network data

So I am working on a new project looking at formal and informal networks between businesses in the same industry. Namely, I am looking at joint ventures, fractional acquisitions, minority share ...
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2answers
598 views

(hierarchical) cluster analysis with non-standard distance

My question is triggered by a question that was asked on stackoverflow: http://stackoverflow.com/questions/12198115/using-different-metric-for-hclust-linkage. The thing is this: I can formulate an ...
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2answers
162 views

How to cluster multidimensional (parametric) distributions?

It seems to me that it is possible to cluster unidimensional distribution in the space of their parameters, for example, we can try to find similar normal distributions in the space of $(\mu,\sigma)$ ...
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4answers
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Appropriate clustering techniques for temporal data?

I have temporal data of activity frequencies. I want to identify clusters in the data that indicate distinct periods of time with similar activity levels. Ideally I want to identify the clusters ...
3
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1answer
3k views

Euclidean Distance b/t unit vectors or cosine similarity where vectors are document vectors

I was reading Similarity Measures and suddenly my whole world was falling apart. I have implemented a search engine using clustering techniques. For clustering, I used k means which uses Euclidean ...
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3answers
2k views

How do I find similarities between two sets of data

I have a group of data with 12 different football players, and they are rated for 11 different skills (speed, skill, flair, etc). I am looking to pair up individuals based on similar footballers, and ...
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2answers
881 views

Specifying the number of clusters in nearest neighbor clustering

I've got a distance matrix between examples. I want to cluster them into m clusters with a nearest neighbor algorithm which works like this: ...
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0answers
129 views

Strategies for Recovering Missing Data

I'm working on the following missing data problem to learn more about stats, probability, and machine learning, but I'm not really making progress solving it: I have a group of unordered, non-unique ...
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1answer
918 views
3
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1answer
771 views

Alternative to Otsu for dividing data into two groups

I need to be able to automatically divide a dataset into two clusters. There are heuristic reasons to expect the data to have two clusters which would be visually clear if one were to plot the data ...
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2answers
2k views

How to calculate the variance of vectors for clustering?

I'm interested in various methods of measuring dispersion of vectors mainly for use in cluster analysis. I can think of three methods: Find the mean vector (centroid), then calculate the variance ...
6
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2answers
4k views

How to 'intelligently' bin a collection of sorted data?

I am trying to intelligently bin a sorted collection. I have a collection of $n$ pieces of data. But I know that this data fits into $m$ unequally sized bins. I don't know how to intelligently choose ...
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1answer
675 views

How can I calculate genetic similarities between groups?

I know how to calculate genetic similarity between genotypes, but I do not know how to calculate genetic similarity between groups. From cluster analysis, I found seven groups. Now, I need to ...
6
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0answers
357 views

Clustering & Time Series

I have a multivariate dataset that changes over time. I have extracted (and normalised) some features and used k-means to generate clusters over the entire span of the dataset. Now I want to see ...