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.

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32 views

clustering high dimentional data (p > n) in R

I have a situation where we have a number of quantitative features / variables (p) than the number of samples (n). My objective is to classify these samples into groups (may be hierarchical). I can ...
2
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1answer
20 views

One-class Classification of multidimensional vectors

I have a m x k User-feature matrix (m >> k) obtained by factorizing an original User-websites matrix (m x n) that has #page views as entries. Additionally, there are users (say r) who have been ...
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1answer
104 views

How to generate new Topic for new documents?

what approach would help me generate new topics for new documents? I read this page in order to learn more about the effect of specifying keywords for the topics that we care about detecting in new ...
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1answer
50 views

hclust, R and Euclidean distances: weird stuff

I have a table of similarities expressed through cosines and am trying to do some cluster analysis in R, using hclust and ...
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1answer
19 views

Metrics for cluster evaluation

I make a set of clusters using some clustering algorithm. Precision, Recall, F Measure, Fallout and RI of individual clusters are calculated for testing the performance. How do I calculate the average ...
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1answer
25 views

Creating a cluster analysis on multiple variables

I am working on creating a cluster analysis for some very basic data in r for Windows [Version 6.1.76]. The groups themselves are countries and then I have 2 column with continuous numerical ...
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1answer
57 views

Finding the cluster centers in kernel k-means clustering

I think this is the most easily understood topic in Kernel K Means Clustering. But assuming that I am not an expert in Machine Learning, can someone tell me how does someone calculate Kernel K means ...
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0answers
14 views

Justifying unsupervised clustering using Random Forest?

I have been looking at ways to carry out unsupervised clustering of data with both numeric and nominal (but not ordinal) variables. I also suspect non-linearity in the data. A possible solution would ...
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0answers
7 views

Datasets for market segmentation

What are the gold standard datasets to test market segmentation algorithms with? I'd like to try a few algorithms on known datasets for comparison before I try my own dataset.
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1answer
33 views

Is there such thing as correlation trees? Clustering rows of X based on correlation between A and B

I have been searching for several days for a method that fits this description, though cannot find one. I'm pretty sure it must exist. The problem (short version): I'd like to run something like a ...
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1answer
17 views

Searching for time series inside another time series

I have a time series "A" and another one "B". I would like to find occurrences of "B" inside "A". Typically, "A" is much bigger (magnitude: millions of points) than "B" (magnitude: hundreds of points) ...
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2answers
34 views

Finding independent “clusters” in a matrix

I've called my question "clustering" but I am not sure if that's the right term. Imagine my matrix looks like this: ...
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4answers
3k views

Clustering 1D data

I have a dataset, I want to create clusters on that data based on only one variable (there are no missing values). I want to create 3 clusters based on that one variable. Which clustering algorithm ...
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0answers
32 views

Groups in linear regression with different intercepts. How do I find the differing variable?

This is more of a conceptual question. I have a coefficient estimate of .80 in a linear regression model with one IV and one dependent variable. However, plotting the data I see distinct groups, ...
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2answers
1k views

LSA vs. PCA (document clustering)

I'm investigation various techniques used in document clustering and I would like to clear some doubts concerning PCA (principal component analysis) and LSA (latent semantic analysis). First thing - ...
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1answer
318 views

Rand index calculation

I'm trying to figure out how to calculate the Rand Index of a cluster algorithm, but I'm stuck at the point how to calculate the true and false negatives. At the moment I'm using the example from the ...
2
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1answer
157 views

PAM with Gower distance matrix

My data is is mostly continuous but has one binary variable. I tried the pam algorithm in R with the Gower index, but the number of clusters that give the best ...
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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 ...
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2answers
44 views

clustering accuracy

I have a general doubt regarding clustering. I have a data set of size 1196*18675. where 1196 is the no of documents. I am trying to cluster the data with k=7 using k-means. Each time the clustered ...
2
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1answer
49 views

Cross-validation for Comparing Clustering Techniques

I'm working on comparing multiple clustering algorithms to each other using the adjusted Rand index for a given dataset. We have a gold standard that we'd like to compare the obtained clustering ...
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0answers
21 views

Using the coefficients of regression for giving weight to the data

I want to perform clustering on my data set. I used spectral clustering and obtained an acceptable result. In an effort to (maybe) improve the result, I thought of applying a linear regression on my ...
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1answer
37 views

Clustering of items based on their category belonging

I am trying to find a clustering algorithm, but I'm working with already classified items. Basically, items belongs to one or more category, which are already known. Categories are absolutely not ...
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1answer
29 views

Classifying a set of photos to places

I want to cluster photos and map them to places. As input I have Photos with locations (lat, long) Places - some as (imprecise) bounding boxes, some just as points, maybe others as bounding ...
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1answer
232 views

F-measure for document clustering evaluation - NaN

I'm developing the Java application for text document clustering, and I'm researching some evaluation methods. I implemented F-measure (http://en.wikipedia.org/wiki/F1_score), but I have a problem - ...
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1answer
32 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
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1answer
31 views

A clustering and classification question

I'm trying to classify my set of data into two classes (introvert / extrovert). I was thinking of using a decision tree at first, but I don't have any potential known results in order to create my ...
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1answer
31 views

Clustering a completely interconnected graph with weighted edges

I was wondering if Markov Clustering is what I really am looking for or not. Basically I have a N node graph in which every node is directly connected with one another. However, all the edges are ...
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1answer
97 views

Pull out most important variables from PCA

I would like to get the most important variables from a PCA result. I see two clusters in the plot. I now that is possible that there is no only one variable causing this, so maybe I would have to get ...
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2answers
147 views

Similarity between objects based on tags (binary features)

I have five millions of objects each of them having one or more tags. How do I compute statistically sound similarity score between each pair of the objects taking into account that: There are 100 ...
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1answer
35 views

cluster analysis, Ward: how to evaluate number of clusters and their quality?

I have a table of similarities (cosines) and I clustered it with the Ward method. Great outcomes, a wonderful dendogram, but then I tried to evaluate the quality of this cluster solution and I got ...
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1answer
35 views

using cluster information in multiple imputation

i need to impute a dataset all categorical variables before doing analysis. I can just simply impute with mode of all data or a variable. I belief that better option will be to classify the subjects ...
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0answers
20 views

Setting up feature vectors

I am working on a classification project and I want to use SVM's and/or Clustering Algs. What I am having trouble with is deciding how to set up my feature vectors. I have already decided what my ...
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1answer
102 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 ...
2
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1answer
118 views

Dirichlet process mixture model with Bayesian hierarchical clustering

I am doing Bayesian hierarchical clustering. From my understanding, there are three basic points for this algorithm. Use marginal likelihoods to decide which clusters to merge Asks what the ...
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1answer
392 views

Cluster analysis on weighted survey data with continuous and categorical variables

I am trying to perform cluster analysis on survey data where each respondent has answered several questions, some of which have categorical answers ("blue" "pink" "green" etc) and some of which have ...
0
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1answer
166 views

How to calculate purity?

In cluster analysis how do we calculate purity? What's the equation? I'm not looking for a code to do it for me. Let $\omega_k$ be cluster k, and $c_j$ be class j. So is purity practically ...
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2answers
92 views

Excel: which products are most frequently ordered together? (clustering question)

I'd like to recruit your help in coming up with an Excel-based method to analyse a set of raw ordering data where each item is on its own row. So, in the data below, order 111 contains two part ...
2
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1answer
103 views

Word clustering using different algorithms

At the moment I'm researching clustering of single words. The input of this research is a list of words (unigrams). During the research I want to compare different clustering algorithms to see the how ...
3
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1answer
123 views

Distance between two Gaussian mixtures to evaluate cluster solutions

I'm running a quick simulation to compare different clustering methods, and currently hit a snag trying to evaluate the cluster solutions. I know of various validation metrics (many found in ...
3
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2answers
244 views

Clustering of points based on vector feature similarities in R

I have as an input a number of points that I need to partition into clusters. Each point has a number of features that are ideally to be used to find the similarity between each point and the others. ...
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0answers
44 views

(Spatial) distance between cluster means

I'd like to cluster points based on a distance criteria. As I want to cluster spatial points I am using euclidean distance and a hierachical cluster approach. In a final step I'd like to cut the ...
0
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1answer
22 views

What method to use for cluster identification ?

This question is from a confused novice. I have a data set with where each point is located in a 2-D space defined by two objectives (say, X and Y). I wish to identify a set of points from this space ...
2
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0answers
26 views

Hierarchical Tobit Model

I'm studying the effect of various criminal case and court district characteristics on sentence lengths. I was planning on running a hierarchical linear model (HLM) of individual defendants/cases ...
0
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1answer
17 views

Need help understanding response from Metis

I was wondering if any of you could help me understand the response I got from this clustering algorithm (Metis). As you probably can see, I'm trying to cluster IP addresses based on common records ...
4
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1answer
287 views

What is the intuition behind the variation of information (VI) metric for cluster validation?

For non-statisticians like me, it is very difficult to capture the idea of VI metric (variation of information) even after reading the relevant paper by Marina ...
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1answer
80 views

Comparison of close data sets

I'm studying around 100 sets of temperature ($N_{sample}=500$), which depends $4$ explicative variables such as power or speed. The dependency is always the same in each set, but sometimes the mean ...
0
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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 ...
0
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1answer
151 views

Gaussian neighborhood function and non linear learning rate for SOM in R

I've been working on SOMs and how to get the best clustering results. One approach could be to try many runs and choose the clustering with the lowest within sum of squared errors. However, I do not ...
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0answers
28 views

Reducing high dimensionality as well as feature selection on multivariate time series

Lately I've been reading a lot about time series clustering as I want to search for similar patterns in my own data set. Even though I feel like I understand the basic concepts of this task I still ...
4
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1answer
539 views

Validate cluster analysis in R

I am trying to validate hierarchical cluster analysis result following a paper by Guy Brock, et al. clValid: An R Package for Cluster Validation (pdf). Do I have to use all these methods? What are the ...