Cluster analysis is the task of 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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Confidence Score for Unsupervised randomForest?

I am using the unsupervised form of randomForest (R) as part of a clustering scheme for 1000 peaks based on 30 features. I use the proximity matrix produced by ...
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26 views

Clustering + SVM -> transductive SVM?

Given a binarily labeled train set, and an unlabeled test set, consider the following two-step classification system: step 1: the train and test data is clustered. step 2: an SVM is fitted for each ...
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42 views

Clustering of Line Graphs

I have a sample of line graphs (like the ones below), and I am trying to find the easiest way to cluster graphs with similar patterns. It would be great to be able to say something like "X% of graphs ...
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84 views

How to calculate the distance between clusters using log-likelihood in two step clustering? [closed]

Log-Likelihood Distance (TwoStep clustering algorithms) How to calculate the distance between clusters(i.e record and cluster) using log-likelihood in two step clustering using the below mentioned ...
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1answer
59 views

Weird Clusplot when plotting k-mediods clustering vector

The basic idea of the problem is that I need to cluster a set of points for which I have a dissimilarity matrix. I have a dataset of around 4600 points (latitudes and longitudes). I have also ...
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1answer
53 views

PCA vs. Spectral Clustering with Linear Kernel

Consider a feature vector matrix $X := [x_1 x_2 \dots x_d] \in \mathbb {R}^{n\times d} $ that I hope to use as part of some supervised learning procedure, say, regression. Suppose that also, $d \gg n ...
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33 views

Summarizing multiple clustering results

I'm working on a problem where observations are being clustered within groups but I'd also like to compare the groups. However I am not sure of the best way to compare the groups. In total I have ...
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1answer
59 views

Combine two, three, (n) metrics for calculating dissimilarity matrix

I have a data set with 9000 instances and 40 attributes of mixed data, that is categorical and numeric. My target is to group them into clusters using whichever clustering algorithm works best. I've ...
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1answer
41 views

How to decide the numbers of row & column clusters for co-clustering

I want to use the blockcluster package in R to perform co-clustering on my data. But the function requires the number of row and ...
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15 views

using histogram distances for clustering

Business context: for our retail client there are a few crucial products. All of them have 3 phases (introduction, stable phase and end of life). After correcting for seasonality and discounts (as ...
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1answer
35 views

cforest - Prediction without labels

I have some data that I want to get the important variables from. I want to use random forest to get this information. The problem is that the data does not have labels. From what I understand random ...
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18 views

Encoding a set of vectors into 1 vector

I have a set $X$ that contains a set of vectors $V_i$ and I want to create a vector $u$ that represents each set. $V_i \in X$, $u$ is a representation of $V_i$. What are the possible ways of doing ...
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61 views

Validate Cluster Analysis by doing it on two subsamples

I am working on validating a cluster analysis. I have read somewhere the approach to cross-validate the cluster analysis. The link of the article is ...
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38 views

Mathematical steps involved in calculating the gap statistic

Can anyone tell me the mathematical steps involved in calculating gap statistic? (That is, without using any external software.) This is my dataset, the output of my cluster analisys: ...
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1answer
31 views

Measure influence of attribues on clustering

I don't have a specific example for my problem and maybe this is trivial, but I want to know how to measure the influence of specific attributes (or dimensions) of a dataset for clustering, like there ...
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32 views

In R package 'cclust' is there an equivalent of 'nstart' option from the 'kmeans' package? [closed]

I am trying to do k-means clustering in R using the cclust package. In k-means clustering, the initial centroid assignment greatly affects the final allocation. The kmeans package has an nstart ...
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38 views

Model-based clustering methods for mixed data types

Are there any model-based clustering algorithms for mixed type data (i.e., with both categorical and continuous variables)? The popular 'mclust' can only handle continuous variables.
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39 views

How does neuralgas clustering work? Why is it better than k-means for handwritten digits?

Recently I tried to cluster the semeion.data file available in UCI repository using kmeans clustering as well as using the ...
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14 views

Finding the stability of selected parameter values?

I have a system (not a predictive model) that will produce four results (R1 to R4) given a set of input data. The system can be tuned using four parameters (P1 to P4). I can find the maximum value for ...
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2answers
26 views

Clustering of binary/nominal variables in one sample

Assume that a medical school classifies its active, full-time students according to their free time activities. By distributing simple questionnaires individuals have to answer whether or not they're ...
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192 views

Clustering with categorical and numeric data [duplicate]

I frequently come across data sets that have both categorical and numeric data. I think this is just a fact of life where the data is not all in one category. I'm basically trying to find some ...
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19 views

A situation where ignoring clustering optimises the Type I and Type II error rates?

I am interested in modelling clustered data with a small number of clusters as follows: $$Y_{ij} = β_0 + β_1X + u_i + e_{ij}$$ (where $_i$ = 1 to 3; $_j$ = 1 to 12); $Y_{ij}$ is our normally ...
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1answer
37 views

Segmentation analysis based on Likert [closed]

I would like to do a segmentation analysis based on a Likert scale survey. I want to ask respondents to rate certain attributes on a scale of 5 points (not valuable at all, not very valuable, neutral, ...
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15 views

feature selection for clustering: wrappers

I am trying to understand if it is correct to perform a feature selection process using a wrapper method (for example using algorithms such as random forest, linear regression etc.) and then to extend ...
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68 views

Markov Cluster Algorithm transition matrix

I am reading the notes on Markov Cluster Algorithm by Kathy Macropol (http://www.cs.ucsb.edu/~xyan/classes/CS595D-2009winter/MCL_Presentation2.pdf) On slide 14/46 the author talks about inflation and ...
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46 views

how to learn / imitate clustering algorithm?

I have a device which every 100 milliseconds receive 15 data-points, and return the same data-points divided into distinct subsets (each of size <= 4), using some unknown logic/method. My end goal ...
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1answer
56 views

Order a correlogram

I have 30 days data, and I am plotting correlogram using corrplot (R package). I have an option to order the correlogram with hclust option and hence I obtain plot as shown on right side of below ...
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2answers
160 views

Using clustering for unsupervised classification (visualizing k-means cluster centers)

I know that the cluster centroid is the middle of a cluster. It's a vector containing one number for each variable, where each number is the mean of a variable for the observations in that cluster. I ...
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76 views

How do i compare two Self Organizing Maps?

I have results (weights) for multiple runs of self organizing map. I am trying to compare these results to check if my algorithm gets to the same solution from different random initial weights. I have ...
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1answer
72 views

Alternate distance metrics for two time series

I have time-series data of different houses. Assume it is power consumption data. Now, I want to cluster the houses following similar power consumption pattern utmost. So, the various distance metrics ...
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14 views

Compact Spatial Clustering with exogen variable

I have a table with 2400 polygons being a partition of a country at a low level. I have as well the population and the area for each polygon, giving me the density of each polygon. I would like to ...
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23 views

Determining dates of regime switches in historical time series

I am interested in determining the dates of regime switches (i.e. starting points of segments of a (univariate) time series that show similar behaviour, such as similar volatility) in a historical ...
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26 views

Identify subgroup similar to another group [closed]

I have 2 groups of people (group2 is much larger than group1). The two groups have these attributes: demographic information and ...
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2answers
72 views

Meaning of this Cluster Analysis

I have 801 households (or customers). I have say 100 features on which I will describe a customer. I have a feature map with me. I now apply K Means algorithm for the value of K say 6. I get 6 ...
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1answer
55 views

Why is K-Means++ SLOWER than random initialization K-Means?

K-Means is an iterative clustering method which randomly assigns initial centroids and shifts them to minimize the sum of squares. One problem is that, because the centroids are initially random, a ...
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40 views

How to interpret the PAM output

I am using the PAM function in R, and I don't understand how to evaluate its output. Whereas in K-means the ratio between the between sum of squares to the total sum of squares already gives a very ...
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1answer
108 views

Normalisation of circular statistics, such as wind direction in degrees, for clustering

I have a set of data points each representing a day and a number of features associated with it: temperature, wind speed, wind direction, humidity... etc. Before the analysis, I am meant to normalise ...
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32 views

What method for grouping documents by topic

I have a corpus of publications in CS divided by year. What I'd like to discover from it is The subject (only one) of each article ( for example testing, software engineering, networking, ...
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1answer
44 views

Metric for residuals in spherical K-means

I am attempting to use the bag-of-words approach to examine a large text data set. I am experimenting with using spherical K-means to cluster either documents or terms with respect to the other. I ...
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62 views

Matching with multilevel data

I've got a dataset where a treatment $W$ has been applied to units $i$ within clusters $c$. $W$ is constant within each cluster. As a component of an algoritm that I'm implementing (which was ...
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14 views

R: Multiple distance functions in clustering

I want to consider different matrices for different variables, e.g., Euclidean for numerical, Hamming for categorical, earth distance for lat-long etc., in clustering, say k-mean clustering. Is it ...
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2answers
256 views

Clustering in data

I have a set of data points $(x,y)$ where $y = f(x)$. My goal is to fit the function $f$ using ols. The choice of function $f$ is quadratic due to domain know-how.The independent variable $x$ exhibits ...
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2answers
340 views

K-means in R, high nstart gives tiny clusters $(n=1)$

I am using kmeans() to cluster standardized scores from a factor analysis in R (20 variables, 919 cases). As R uses random cases for the initial centroids, I was ...
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87 views

Truncated Dirichlet process vs Dirichlet distribution

As the topic suggests I was wondering what the main differences are in using one over the other. Suppose for sake of simplicity the Dirichlet distribution has all parameters set to $\alpha$. All I ...
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4answers
765 views

How to understand the drawbacks of Hierarchical Clustering?

Can someone explain the pros and cons of Hierarchical Clustering? Does Hierarchical Clustering have the same drawbacks as K means? What are the advantages of Hierarchical Clustering over K means? ...
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1answer
29 views

Longitudinal Cluster Analysis

I have data with subjects, 4 observations each, ordered by time (4 time points each). And, I have some additional numerical variables. I want to perform a cluster analysis to see if there are any ...
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70 views

How to cluster/analyze effect sizes after meta-analysis? (meta-meta-analysis)

For a research project I compared persons with and without a specific disorder on basically every published outcome I could find. The idea was to get some sort of profile of this disorder (i.e. skills ...
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44 views

Cluster the tweets using important hashtags

i extract and rank a list of the important hashtags (using td-idf ) from the twitter dataset(twitter.csv) that just includes list of tweets and now i have 9 important hashtags, now i want to use those ...
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48 views

Preprocessing survey data for clustering

I want to find 4-10 clusters in survey data with 100 questions answered by 2000 individuals using a technique such as K-means or Gaussian Mixture Models. There is no response variable so the ...
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137 views

Multiple eigenvectors in graph spectral clustering

In Newman's PNAS 2006 paper Modularity and community structure in networks, the first eigenvector splits the graph in two clusters, and then each cluster can be further divided by eigenvector of a ...