1
vote
1answer
35 views

Extract (ultrametric) distances from hclust or dendrogram

How can the matrix of (ultrametric) distances be extracted from the result of hclust (or a dendrogram in general) in R? The ...
0
votes
0answers
63 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...
0
votes
0answers
36 views

How to test the significance of clusters?

How can one test the significance of the clusters obtained after a clustering procedure? Are there separate tests for the distance/similarity/dissimilarity measure used to get the distance matrix and ...
-1
votes
1answer
57 views

Cluster with distance threshold in R

I'd like to get clusters with a maximum inner distance threshold. Now I use hc <- hclust(d) and cutree(hc, numofclasses). ...
0
votes
1answer
32 views

string clustering: similarity criterion

I have a set of strings of dimension $10,000$. I want to group similar strings together in one group, perform clustering. As string metric, I am using the ...
0
votes
1answer
195 views

Use of a Poisson distribution from a distance matrix to determine dbscan parameters

I´ve been researching about automatic determination of parameters for DBSCAN (a density-based clustering algorithm -- http://en.wikipedia.org/wiki/DBSCAN), especially eps, and have found the following ...
0
votes
1answer
249 views

distance measure of angles between two vectors, taking magnitude into account

Suppose I have two vectors, v1 and v2, from which I can calculate the angle between these two vectors as a measure of their ...
1
vote
2answers
737 views

How to standardize data for hierarchical clustering?

When running hierarchical clustering analysis of a matrix of individuals x samples (e.g., employee performances across different days), there are several ...
2
votes
0answers
42 views

Creating statistically similar sequences

I have to run a test on a program, with some statistical tools to make sure its results are statistically acceptable. This program will take sequences of data information (a vector of integers or ...
4
votes
2answers
144 views

What distance method to use in this scenario?

I have a 10 dimensional space which contain points that contain a 1 or 0 . example of two points : point1 : 1,1,1,0,0,0,1,1,0,1 point2 : 1,0,1,0,0,0,1,0,0,0 ...
3
votes
2answers
628 views

What are distances between variables making a covariance matrix?

I have a $n \times n$ covariance matrix and want to partition variables into $k$ clusters using hierarchical clustering (for example, to sort a covariance matrix). Is there a typical distance ...
9
votes
2answers
294 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
1answer
273 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 ...
5
votes
1answer
378 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
444 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
344 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
116 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
362 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
357 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: ...
13
votes
7answers
2k views

How to perform k-means clustering with only a distance function, not euclidean points?

I want to perform k-means clustering 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
850 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
2k 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
142 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 ...
3
votes
1answer
2k 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
595 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 ...
5
votes
1answer
541 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
4answers
357 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 ...