2
votes
0answers
27 views

Good (2d) visualization of a mixture model clustering

I have a specific problem which I'm surprised I don't find answers on-line and I hope somebody here has a good suggestion for me. I'm working with a large data set which I'm clustering into specific ...
2
votes
2answers
94 views

How can I cluster data in a grid-like fashion and heat map the averages in R?

I have a data frame of 3 columns. The first one is the response variable the second and the third ones are some criteria. You can create your own example similar to mine, using this piece of code with ...
0
votes
0answers
147 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 ...
0
votes
1answer
52 views

Interpretation of NbClust result

The plots show the output of NbClust(). By looking at the plot, is that correct to say that k=5 is the optimal number of ...
1
vote
1answer
34 views

How do multi-attribute edge-weights influence community detection?

My graph consists of a computer network topology where each vertex is a physical node/device (depicted using its IP address). Two vertices will have an edge if the nodes have had communication with ...
0
votes
1answer
98 views

Hierarchical clustering of correlation matrix

I have a correlation matrix of 8,854 * 8,854 size. These are Pearson correlation coefficient values in the matrix. I want to perform Hierarchical clustering and create good resolution images like I ...
3
votes
1answer
57 views

Finding clusters to fit least squares and produce a piecewise equation

In the figure below, I've manually drawn an approximate solution to a least squares fit of the associated regions separated by black lines. The data appears to be bounded by two asymptotes (y=-18 and ...
0
votes
1answer
261 views

Multidimensional scaling using Python

I have 6,000 points for which I have all pairwise distances in a distance matrix. I want to get an idea whether these data were generated by a mixture of Gaussian distributions so I'm trying to get a ...
5
votes
1answer
239 views

Interpret clustering plotted in the first two principal components

I got this plot when I plotted a clustering object in R. If I run km <- clara(data, 2), then plot(km), I get a similar ...
1
vote
3answers
132 views

Which analysis for a set of (0/1)binary variables alone?

I have a dataset I would like to analyze and plot It consists of 100 binary variables (0/1) for about 2,000,000 observations There is absolutely no quantitative variable, nor anything I could use as ...
2
votes
2answers
182 views

Does Newman's network modularity work for signed, weighted graphs?

The modularity of a graph is defined on its Wikipedia page. In a different post, somebody explained that modularity can easily be computed (and maximized) for weighted networks because the adjacency ...
1
vote
2answers
813 views

Clustering with Weka

Hi everyone and happy new year! I have to analyse a data set with weka clustering, using 3 clustering algorithms and I need to provide a comparison between them about their performance and ...
1
vote
0answers
38 views

What is exactly code vector and quantization vector of self organizing map?

I am trying to understand code vector in self organizing map. Could anybody explain me intuitively what it is exactly?
4
votes
1answer
42 views

Clustering data for occurrence

I have a set of data representing nodes and how often they have been involved with each other. I've processed this into a table containing the nodes on X and Y with the data being the number of ...
0
votes
1answer
118 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? ...
2
votes
1answer
362 views

Interpretation of PCA biplot?

I just ran my first ever PCA, so please excuse any naivety on my part. As input, I used five years worth of the following: S&P/ASX 200 A-REIT S&P/ASX 200 Consumer Discretionary S&P/ASX ...
1
vote
1answer
44 views

Weighing probabilities into a polygon

I have a collection of 4-member probability vectors (essentially proportions over 4 mutually exclusive categories). Is there a method to represent this data as a cloud of points inside a square? If ...
1
vote
2answers
1k views

K-Means Clustering - Calculating Euclidean distances in a multiple variable dataset

I have just completed a simple exercise with 2 variables (X and Y) to understand how K-Means clustering works. The results look like this, My questions is, if I have another column Z, how should ...
3
votes
1answer
133 views

How to properly color clusters for visualization

I've some data that I can express as an image. Within this data I found some clusters (shown in the image below). I can just assign different colors to different clusters and visualize the image but ...
-1
votes
1answer
87 views

Cluster centroids visualization

I've some data that I've clustered and calculate the similitude within my cluster centroids to spot which class centroids are close to which ones. My goal was to visualize this as a map of points. I ...
0
votes
2answers
59 views

Clustering cloud fitting inverse functions

I have a cloud of points that can be clustered so that each set of points in the cluster can be fitted with an inverse function : $f(x) = cte / x$. What would be an approach for clustering my dataset ...
0
votes
1answer
91 views

Three-dimensional phylogenetic tree “anchored” in a scatter plot

I have done a simple clustering (protoclust) using error-containing data. To determine distances, I used a simple "pseudo-d" distance, in which the absolute value of the difference between two points ...
2
votes
0answers
355 views

Sorting/Clustering similarity matrices

I wonder, what are the available libraries in R or Python to do correlation matrix clustering (sometimes it is referred to clustering). I also, wonder, after clustering/grouping each point. What is ...
0
votes
1answer
735 views

Interpreting Cluster Heat Maps From R

So I have been looking at how to plot high dimensional clustered data, and one of the options that come up is a heat map. Although there are many webpages that provides code on how to create one, ...
3
votes
2answers
449 views

Visually plotting multi dimensional cluster data

I have a data set with 16 variables, and after clustering by kmeans, I wish to plot the two groups. What plots do you suggest to visually represent the two clusters?
5
votes
3answers
194 views

Rounding when making a histogram

Suppose that when making a histogram, one encounters a datum at a bin boundary. Is there a convention on how to round it? For example, suppose my data are integer percentages, running from 0% to ...
3
votes
2answers
898 views

R: Visualizing document clustering results

I have a k-means clustering result with 35 clusters, there are 5000 documents that each belong to one of the 35 cluster. I would like to visualize the results of the clustering algorithm on a scatter ...
5
votes
1answer
302 views

Index plot for each cluster sorted by the silhouette

After a cluster analysis I´m trying to plot for each cluster the Index plot of the Silhouette value instead of for the complete dataset (like in the WeightedCluster Library Manual by Matthias ...
2
votes
0answers
203 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 ...
8
votes
2answers
335 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
1answer
740 views
4
votes
2answers
598 views

Appropriateness of PCA to visualize clusters in genetic data

I've seen PCA improperly applied in genetic research quite often. I wanted to clarify : when is it appropriate to use PCA as a visualization tool in your analysis? Some examples: 1) Rarely is the % ...
2
votes
1answer
70 views

Plotting decay in clustering?

I've got a method that produces clusters of elements and singletons. The singletons usually comprise about half of the initial element set, and there usually is a single biggest cluster of a several ...
3
votes
6answers
1k views

Looking for 2D artificial data to demonstrate properties of clustering algorithms

I am looking for datasets of 2 dimensional datapoints (each datapoint is a vector of two values (x,y)) following different distributions and forms. Code to generate such data would also be helpful. I ...
4
votes
0answers
76 views

R: looking for “time” clusters in a data set

I am new to R and seeking some advice. I have a set (~20M) of data describing on which step a process did fail or succeeded: ...
4
votes
2answers
969 views

How to plot results from text mining (e.g. classification or clustering)?

In text classification and clustering, the number of features are normally big, e.g. I currently get are around 5,000 features which is already really small compared to many other text mining tasks. ...
3
votes
0answers
322 views

Cluster similarity percentages with inverted Y-axis in R

I'd like to ask a question here that I've also asked on Biostar (stackexchange) and someone there forwarded me to this website. I was wondering how I could perform a Bray Curtis similarity clustering ...
7
votes
5answers
464 views

Dimensionality reduction technique to maximize separation of known clusters?

So let's say I have a bunch of data points in R^n, where n is pretty big (like, 50). I know this data falls into 3 clusters, and I know which cluster each data point is a part of. All I want to do is ...
7
votes
2answers
1k views

Visualizing multi-dimensional data (LSI) in 2D

I'm using latent semantic indexing to find similarities between documents (thanks, JMS!) After dimension reduction, I've tried k-means clustering to group the documents into clusters, which works ...
15
votes
3answers
5k views

How to interpret mean of Silhouette plot?

Im trying to use silhouette plot to determine the number of cluster in my dataset. Given the dataset Train , i used the following matlab code ...
5
votes
3answers
3k views

How to plot data output of clustering?

I tried clustering a set of data (a set of marks) and got 2 clusters. I would like to graphically represent it. Bit confused about the representation, since I don't have the (x,y) coordinates. Also ...
5
votes
3answers
645 views

How to generate user-friendly summaries of cluster analysis?

I used BIRCH and HAC to do clustering on my data. I want to now what type of information I can include in reports that my users can generate to get more insights on the clusters. I would have to dumb ...
4
votes
3answers
3k views

Plotting a heatmap given a dendrogram and a distance matrix in R

I have dendrogram and a distance matrix. I wish to compute a heatmap -- without re-doing the distance matrix and clustering. Is there a function in R that permits this?
6
votes
1answer
1k views

Interpreting output of igraph's fastgreedy.community clustering method

With the help of several people in this community I have been wetting my feet in clustering some social network data using igraph's implementation of modularity-based clustering. I am having some ...
21
votes
7answers
7k views

How to do community detection in a weighted social network/graph?

I'm wondering if someone could suggest what are good starting points when it comes to performing community detection/graph partitioning/clustering on a graph that has weighted, undirected edges. The ...
7
votes
2answers
2k views

Newman's modularity clustering for graphs

I am interested in running Newman's modularity clustering algorithm on a large graph. If you can point me to a library (or R package, etc) that implements it I would be most grateful. best ~lara
13
votes
8answers
2k views

Visualization software for clustering

I want to cluster ~22000 points. Many clustering algorithms work better with higher quality initial guesses. What tools exist that can give me a good idea of the rough shape of the data? I do want to ...