Tagged Questions

4
votes
1answer
88 views

Finding a known number of circle centers that maximize the number of points within a fixed distance

I have a set of 2-D data where I want to find the centers of a specified number of centers of circles ($N$) that maximize the total number of points within a specified distance ($R$). e.g. I have ...
0
votes
2answers
52 views

Non-distance metrics in hierarchical clustering? [closed]

What happens, intuitively, when one uses non-distance metrics to calculate the distance matrix that feeds into a standard hierarchical clustering algorithm? What mistakes will the algorithm make and ...
0
votes
1answer
159 views

KL divergence or similar “distance” metric between two multivariate distributions

I have a large dataset composed of many samples; each sample is as follows: imagine a grid indexed by i,j for a sample k, I have Y_k, where Y_k(i,j) is the probability density for k at (i,j) of ...
3
votes
1answer
120 views

What are the use cases related to cluster analysis of different distance metrics?

I'm trying to use different distance metrics like Euclidean, Manhattan, cosine, chebyshev among other distance metrics in my k-means algorithm to calculate distances between the data points and the ...
1
vote
1answer
180 views

Does Mahalanobis distances have “significance” associated with them?

I have a "distance matrix". let's say a 6x6 distance matrix, each cell is the Mahalanobis distance of two "clusters" (or sets/groups of things in a multidimensional space), I want to "count" the ...
1
vote
1answer
88 views

Cluster analysis with skewed distibutions

For my master's thesis I would like to use different clustering algorithms to cluster municipalities (as objects) in regard to their land-use characteristics (as variables). Analyzing my data ...
2
votes
2answers
87 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 ...
2
votes
2answers
158 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 ...
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: ...
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 ...
2
votes
0answers
292 views

Distance threshold for clustering

Usually online clustering methods (based on kmeans or not) define a distance threshold value. If a new data-point $x$ is far enough from the nearest center $c$ (i.e. the distance from $x$ to $c$ is ...
0
votes
3answers
701 views

Using a cosine similarity does not work for any dataset

I have a clustering algorithm, where if I use an euclidian distance as similarity, it works well on any dataset. If I replace it by a cosine similarity (see my code bellow), it will give a degenerate ...
2
votes
0answers
102 views

Use of autoregressive metric for ARIMA clustering and analysis

I wonder if anyone has put into use the autoregressive metric for ARIMA clustering proposed by Corduas and Piccolo (2008). The authors define the distance autoregressive metric between two processes ...
2
votes
1answer
774 views

Gower's dissimilarity index

I would like to ask a question about Gower similarity/dissimilarity index. Is it ok to use the Gower dissimilarity measure with Ward linkage clustering? I was reading that the Gower similarity index ...
1
vote
2answers
346 views

Can I use log-likelihood distance on data of only continuous variables?

I have to run a SPSS two-step cluster analysis. All my 4 variables are continuous scalar standardized parameters (with normal distribution). The dataset includes 10,000 cases. SPSS suggest to use ...
3
votes
1answer
313 views

Clustering with some cluster centers fixed/known

Thanks for reading my question. I have several thousand data points scattered on an (x,y) grid that I am trying to cluster. The data points are not uniformly distributed across the grid, but are ...
7
votes
2answers
202 views

Clustering with asymmetrical distance measures

How do you cluster a feature with an asymmetrical distance measure? For example, let's say you are clustering a dataset with days of the week as a feature - the distance from Monday to Friday is not ...