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.
1
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3answers
131 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 ...
2
votes
1answer
256 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 ...
0
votes
1answer
90 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 ...
0
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0answers
39 views
How can I evaluate the clusters that result from sequence alignment?
I used sequence alignment to find the similarities among a set of objects, then used agglomerative clustering to cluster the sequences. At the same time I used another way for clustering the ...
1
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4answers
1k 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 ...
4
votes
3answers
853 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 ...
0
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2answers
47 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 ...
1
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3answers
99 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 ?
6
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1answer
198 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 ...
2
votes
2answers
151 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 ...
2
votes
1answer
113 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.
...
0
votes
1answer
73 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
votes
1answer
70 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, ...
1
vote
1answer
73 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 ...
3
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1answer
83 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 ...
2
votes
2answers
160 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 ...
0
votes
0answers
44 views
How do I group similar competitors based on flight origin and destination prices?
Suppose we want to look at which airlines have similar pricing strategies. The data set looks like this:
...
1
vote
2answers
121 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 $(\mu,\sigma)$ ...
9
votes
5answers
293 views
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 ...
2
votes
1answer
604 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 ...
4
votes
3answers
483 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 ...
1
vote
2answers
166 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:
...
2
votes
0answers
81 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 ...
2
votes
1answer
451 views
2
votes
1answer
137 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 ...
2
votes
2answers
254 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 ...
3
votes
2answers
372 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 ...
1
vote
1answer
175 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 ...
0
votes
0answers
83 views
Can I use multi-response permutation procedure test on the entire likert scale score dataset?
I have a dataset from a 7-point likert scale scores of 30 questions asked to 145 individuals. I would like to know if I can use MRPP on the entire dataset to test for difference between different ...
3
votes
0answers
122 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 ...
0
votes
0answers
21 views
How do I determine the number of natural groupings within a dendrogram in 'R'?
The data I have clustered is: $n$ number of replicates in rows and 11 different dolphin surface behaviour types in columns as the variables.
I have carried out a hierarchical cluster analysis using ...
1
vote
2answers
53 views
How to measure clustering in time duration?
I wish to measure clustering in the duration between stock trading. For example, a trade occurs at 1:59:19 and the next trade follows at 1:59:23 - the inter-trade duration is 4 seconds. I have roughly ...
2
votes
1answer
142 views
Fuzzy C-means and its stages of clustering
when dealing with soft and hard clustering techniques such as K-means and fuzzy C-means I run into abit of difficulty on the steps that FCM takes to calculate the clusters.
For instance in K-means ...
1
vote
1answer
167 views
Market / Customer Segmentation - Merging two different segmentations
I have a database where each observation is a person. They were questioned on their attitude towards the consumption of X category of product. I have being using K-means to segment this data.
I have ...
5
votes
1answer
216 views
How to statistically test whether there is any nesting effect in the data?
I have a sample including all students within 52 schools which have been randomly assigned to be treatment or control (we have group randomized trial in which all students in each school is either ...
1
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2answers
264 views
Hybrid (K-means + Hierarchical ) clustering
I have a huge dataset (50,000 2000-dimensional sparse feature vectors). I want to cluster them in to k (unknown)clusters. As hierarchical clustering is very expensive in terms of time complexity ...
-1
votes
2answers
66 views
Is there an analytical function that approximates number of clusters?
I have a dataset {x_i} which form 3-10 clusters. Is there any analytical function of {x_i} that I may use to estimate the number of clusters in the dataset?
The fact that there might be 3-10 clusters ...
2
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2answers
99 views
3
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0answers
165 views
On cophenetic correlation for dendrogram clustering
Consider the context of a dendrogram clustering. Let us call original dissimilarities the distances between the individuals. After constructing the dendrogram we define the cophenetic dissimilarity ...
8
votes
7answers
1k views
How to perform k-means clustering with only a distance function, not euclidean points?
I want to perform k-means clusteirng on some objects I have, but the objects aren't described by "points". However, I am able to compute the distance between any two objects (it is based on a ...
4
votes
1answer
148 views
Cluster clickstream data
I've recently entered the realm of machine learning and a project I am working on requires me to cluster users based on the order they visited webpages on a website. I have data in the form of:
...
5
votes
1answer
569 views
BIC or AIC to determine the optimal number of clusters in a scale-free graph?
I am currently trying to partition a scale-free ("big") graph (around 20k vertices, 500k edges) into appropriate sub-graphs. Having derived the Laplacian of the graph, I tried running an approach ...
4
votes
1answer
341 views
Fuzzy K-means - Cluster Sizes
I'm trying to do fuzzy k-means clustering on a dataset using the cmeans function (R) . The problem Im facing is that the sizes of clusters are not as I would like them to be. This is done by ...
9
votes
2answers
137 views
Detecting Clusters of “similar” source codes
Assume I have 400 students (that's in a big university) that have to do a computer science project, and that they have to work alone (no group of students). An example of project could be let ...
3
votes
2answers
94 views
How do I cluster data where some observation can not be in the same cluster?
Say I have 12 (x,y) positions:
...
3
votes
2answers
271 views
How is approximately unbiased bootstrap better than a regular bootstrap with regards to hierarchical clustering?
I asked this question at BioStar but did not get a reply, so Im posting the question here.
What is a simple explanation of what an approximately unbiased bootstrap is with regards to hierarchical ...
4
votes
1answer
616 views
Is there an R function that will compute the cosine dissimilarity matrix?
I would like to make a heatmap with row clustering based on cosine distances. I'm using R and heatmap.2() for making the figure. I can see that there's a ...
2
votes
4answers
423 views
Clustering as a means of splitting up data for logistic regression
I'm trying to predict the success or failure of students based on some features with a logistic regression model. To improve the performance of the model, I've already thought about splitting up the ...
2
votes
1answer
134 views
Multiplicity in sample size calculation for stratified estimation problem
We want to determine the public opinion about a recently administered intervention in a health care network. There's a brief questionnaire of 10 Y/N questions in which we'd like to estimate ...
1
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0answers
51 views
What is an appropriate classification method for analysis of down-hole geophysical data?
I am looking for a method that may be used to classify and 'cluster' some multi-dimensional data gathered from drill holes, to impute some (only partially measured) physical properties of the rocks ...
