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.

learn more… | top users | synonyms (1)

4
votes
1answer
103 views

Clustering data that has mixture of continuous and categorical variabes

I have data that represent some aspect of human behavior. I want to cluster it (unsupervised) into behavioral profiles of some sort. now, some of my variables are categorical (with 2 or more ...
3
votes
1answer
128 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 ...
0
votes
0answers
12 views

Appropriate PCA/ EFA rotation method

Question about appropriate PCA/ EFA rotation method. While I see that oblique rotation methods (e.g. promax) are suggested for correlated data (and I have correlated data) I see that the majority of ...
0
votes
0answers
20 views

Cluster Matching/comparison

Description I have several datasets(from different subjects) with the same type of data. For each dataset I cluster the data using affinity propagation. Clustering is based on similarity distance ...
1
vote
1answer
25 views

Binomial data and PCA and cluster analysis

I have obtained responses on around 48 items measuring employer attractiveness. The goal of my analysis is to cluster respondents according to these employer attractiveness dimensions. I plan to ...
2
votes
1answer
64 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 ...
2
votes
1answer
165 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 ...
0
votes
1answer
15 views

Correlation or clustering of continuous score and discrete variable states

I have an experiment that produces a decimal score representing quality, and a bunch (5-30) of variables that each take on one of a set of discrete states. - The states are not meaningfully ...
0
votes
0answers
4 views

Streaming k means clustering Mahout

First of all, excuse me if this is not a good place to ask this question. Can anyone explain to me how streaming kmeans algorithm implemented in Mahout works? And can it be used for anomaly ...
1
vote
1answer
107 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 ...
0
votes
1answer
21 views

How can I determine local minima from a Kernel Density Estimation? [duplicate]

I have a fairly large 1-dimensional array that I am trying to cluster. I came across several other questions on this site where the top answer is to use a Kernel Density Estimation and then locate ...
0
votes
0answers
9 views

Term to Describe Strongly Clustered Data

I have some data which are strongly gathered into more than one cluster. I am looking for a term to effectively describe this phenomenon: e.g., multi-clustered data, which however seems to me that we ...
0
votes
1answer
245 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 - ...
1
vote
2answers
154 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 ...
0
votes
1answer
93 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 ...
0
votes
1answer
22 views

Mixing probabilities in mixture models using EM

Assume we want to estimate the mixing probabilities ($\pi_{k}$) for each member distribution in the mixture model. We know that $\sum_{m}^{K}\pi_{m}=1$, so we can formulate the optimization problem ...
4
votes
2answers
50 views

Using k-means with other metrics

So I realize this has been asked before: e.g. What are the use cases related to cluster analysis of different distance metrics? but I've found the answers somewhat contradictory to what is suggested ...
5
votes
1answer
377 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 ...
2
votes
1answer
60 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 ...
0
votes
1answer
29 views

How to Calculate silhouette coefficient in SPSS for clustered data set?

I am having a pre clustered dataset with data and the action cluster identified for it using a custom clustering method. I am looking to calculate silhouette coefficient on this clustered dataset ...
0
votes
0answers
21 views

breakpoint analyses on multiple series: how to detect common points

I have 20 time series that span the same period (100 days each), from 4 species sampled at 5 different location. I made a loop to perform a breakpoint analysis on all of them, resulting in 0 to 3 ...
0
votes
2answers
43 views

What's a good way to mentally visualize n dimensions in a k means

I've been using k-means to do some clustering and one of the ideas I'm struggling with is the n dimensions aspect. If I were clustering housing prices vs sq. feet its just a simple 2d graph. That I ...
0
votes
1answer
19 views

Is my understanding of how to calculate the reachability distance in local outlier factor correct?

Reading lof implementation at : http://www.cse.ust.hk/~leichen/courses/msc-it5210/lectures/LOF_Example.pdf the local reachability distance is given as : I don't fully understand this equation as ...
0
votes
0answers
7 views

Clustering techniques when there are two distinct but numerically similar clusters among others

I'm trying to cluster some spatial statistics for some behavioral estimation. However, parts of the trajectory report exactly 0 speed, which implies some kind of resting state which is different from ...
0
votes
1answer
220 views

SSB - Sum of squares between clusters

I got a little confused with the squares and the sums. As far as I know, the variance or total sum of squares (TSS) is smth like $\sum_{i}^{n} (x_i - \bar x)^2$ and the sum of squares within (SSW) ...
2
votes
1answer
440 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 ...
2
votes
1answer
55 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 ...
1
vote
1answer
13 views

Why is it called Epsilon for DBSCAN?

The two parameters of DBSCAN are epsilon and minimum samples. Shouldn't epsilon be called like "Circle radius"? Why is it called epsilon?
0
votes
1answer
153 views

Outlier detection using clustering and dissimilarity matrix in R

I have some problems in finding the outliers using clustering. The data.frame is ~20000 observations and each row has mixed types of variables(numeric, nominal and binary). What I want to do is to ...
4
votes
2answers
735 views

Fuzzy K-means - Cluster Sizes

I'm trying to do fuzzy k-means clustering on a dataset using the cmeans function (R) . The problem Im facing is that the sizes of clusters are not as I would like them to be. This is done by ...
2
votes
1answer
139 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 ...
0
votes
1answer
104 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 ...
0
votes
0answers
18 views

How to measure the similarity of k-means clustering using different datasets?

I run k-means clustering on my dataset (100 samples in total) and partition the data into k=5 clusters. Then I want to test how robust of the k-means can be; however, I haven't got more new data ...
3
votes
2answers
904 views

How to explain the connection between SVD and clustering?

Is there an intuitive explanation for how SVD is related to co-clustering when performing SVD on a covariance matrix? (i.e. the SVD is performed on the matrix $E[X Y^{\top}]$ where $X \in ...
0
votes
0answers
8 views

automatic assign class name based on text

My question is , I have a set of plain text , i want to create category based on the text. Eg: i have written something about Soup recepie then the algorithm must create a category called Food. After ...
0
votes
0answers
21 views

How can I evaluate the accuracy of a clustering when I don't have information on the true class labels?

Already classified data set for the t-shirt factory problem I want to calculate the accuracy of my algorithm. I have the training data without any size information and I couldn't find the classified ...
4
votes
1answer
586 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 ...
3
votes
1answer
113 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 ...
0
votes
1answer
244 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 ...
0
votes
0answers
15 views

Need a rigorous statistical framework for automating visualization

I am faced with a challenging problem. Suppose I have a large dataset with many attributes and I can filter the data using a set of attributes. The problem is in the event we have a large number of ...
2
votes
0answers
31 views

Order and similarity measurement

Let's say I have 10 different groups, and each group has its own string sequence. So, it should be like: ...
2
votes
1answer
90 views

I've been trying to wrap my head around the use of eigenvalues in cluster analysis. What does it tell me about my clustering behavior?

In a typical hierarchical cluster output from using SAS, the first table given lists all of the eigenvalues. From what I understand, eigenvalues are derived from covariance between the variables. ...
7
votes
1answer
357 views

Selecting an appropriate machine learning algorithm?

I do not think that this is a difficult question, but I guess someone needs experience to answer it. It is a question that is asked a lot here, but I did not found any answer that explains the reasons ...
2
votes
2answers
82 views

How does one go about clustering data?

(I have updated the question following conversation with @whuber in the comments). My case is as follows: I have around one thousand row vectors of dimension $1 \times 8$. These row vectors are ...
4
votes
1answer
112 views

how to discard values that are far from center of cluster in mixture model

I am trying to fit a bivariate cluster model with X and Y. What I would like to do is discard (make not clustered / un-grouped) that are far from the cluster center (for example $\mu$ + 2*standard ...
3
votes
2answers
266 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. ...
0
votes
0answers
43 views

Clustering method that can use graph links, discrete and continuous properties?

I have an un-weighted, directed graph that clusters ok using MCL or other graph clustering algorithms. However, I also have additional discrete and continuous properties of the nodes being clustered ...
8
votes
1answer
106 views

Nonparametric mixture model and clusters

I have a question about clusters that I am contemplating to treat with a nonparametric mixture approach (I think). I am working on the explanation of human comportment. Each row of my database ...
2
votes
2answers
88 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 ...
2
votes
0answers
28 views

Co-occurrence statistics for sets

I am looking for help in the following situation: I have a set of numbers $A=\{1, 2, \dots, 100\}$, and I am drawing subsets of 10 of these numbers $\{a_1, a_2, \dots, a_{10}\}$ according to an ...