Tagged Questions

41 views

Is it posible to perform the inverse of multidimensional scaling analysis

We have lot of 3D data and we reduced it to 2D for performing fuzzy clustering and obtaining prototypes. We used some matlab functions that were very well documented. Now we would like to see to which ...
42 views

Implementation for Co-Clustering

I am looking for existing implementations for co-clustering (aka biclustering). I came up with biclust function available in MATLAB, but still I am wondering if ...
304 views

How to plot Optics Clustering result in Matlab (reachability plot)

I modified the following script for Optics clustering ( http://chemometria.us.edu.pl/download/OPTICS.M ) in order to work with DTW distance instead than Euclidean's. I obtained the Order vector ...
19 views

clustering of singular values

let us consider following graph of singular values i want to make some kind of clustering of these data,namely to seperate main components from non main components,let say signal components ...
66 views

Performing hierarchical clustering on a large data set

I have been applying complete linkage on about 5,000 points using matlab with no problem. I want to extend this method to much more elements. It would take me a long time to process my data to test ...
77 views

How to form Clusters from a Similarity Matrix in Matlab

I have a matrix stored in the matlab workspace that has similarity measures between documents stored using one of the similarity measure algorithm. Now, I want to identify the elements which have ...
663 views

Differences between clustering and segmentation

I have read about piecewise aggregate approximation (PAA) mining time series data, sliding window, top down and bottom up approaches for time series segmentation but these are applicable to single ...
121 views

Neighborhood analysis in Matlab using a dot plot

I have points in a 2D graph (coordinates: X,Y property: Z). I would like to find for every point the closest, for example, 5 points and save their properties. What would be the easiest approach? ...
678 views

Calculate BIC to determine the optimal number of clusters (k-means clustering)

I have a set of data and want to know whether they fall in 1, 2 or 3 groups. I started exploring the question by using k-means in MATLAB. By just looking at the distance from the centroid of each ...
55 views

Performance difference in clustering algorithm

I have a similar problem area as mentioned Trajectory Clustering: Which Clustering Method? . As per suggestion to use dynamic time warping for aligning the time series, are there any differences in ...
229 views

K-means clustering for usage profiling

I am trying to use k-means clustering to profile mobile device usage behaviour for IT users. My data consists of different system and user level variable/readings like number of calls/sms, cpu/memory ...
195 views

Representative point of a cluster with L1 distance

The representative point of a cluster or cluster center for the k-means algorithm is the component-wise mean of the points in its cluster. The mean is chosen because it helps to minimize the within ...
88 views

Principal Component Analysis (PCA) for binary data [duplicate]

First of all, I would like to note that I have read similar topics in CrossValidated but I am not fully satisfied. I have a dataset which consists of an $N\times M$ binary matrix. 1 means that an ...
135 views

Representing categorical data in a hybrid dataset

I'm using Matlab to discover some clusters in a dataset that has both numerical (e.g., \$) and categorical (e.g.,zip code) variables. I know some tools can handle categorical variables as factors but ...
2k views

Numerical Instability of calculating inverse covariance matrix

I have a 65 samples of 21-dimensional data (pasted here) and I am constructing the covariance matrix from it. When computed in C++ I get the covariance matrix pasted here. And when computed in matlab ...
485 views

Dimension reduction for sparse matrix for clustering

I'm looking for a Sparse matrix dimension reduction. I already used some feature selection methods like PCA but it doesn't give me good results. I want to apply mixture models for clustering my data. ...
3k 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 ...
920 views

Cluster quality measures

Does Matlab provide any facility for evaluating clustering methods? (cluster compactness and cluster separation. ....) Or is there any toolbox for it?
562 views

How to interpret “weight-position” plot when using self-organizing map for clustering?

I used MATLAB neural network toolbox to train a self-organizing map for a given data set. The obtained "weight-position" plot is given as follows. I do not think this plot looks good in comparison to ...
413 views

Performance of the fuzzy c-means clustering algorithm

I have implemented a genetic algorithm for a fuzzy c-means clustering in Matlab. Its performance should be apriori better than that of the classic fuzzy c-means (fcm function in matlab). However, on ...
6k views

k-means implementation with custom distance matrix in input

Can anyone point me out a k-means implementation (it would be better if in matlab) that can take the distance matrix in input? The standard matlab implementation needs the observation matrix in input ...
851 views

Gap statistics MATLAB implementation

Does any know the reference/link where i can find the MATLAB implementation of gap statistics for clustering as mentioned in this paper?