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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How do I cluster 3 columns of categorical data? [closed]

I am trying to form clusters from my data that is purely categorical: Here's an example: ...
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25 views

Is there a clustering method that can deal with levels/grouping

I have a matrix of pearson correlations that I would like to cluster on similarity and identify correlated networks. However the variables are part of groups and I'm not interested correlations within ...
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1answer
59 views

good practice for cluster analysis [closed]

I want to find out what are the best practice in conducting a reliable cluster analysis: Outliers: Is it necessary or not to remove the outliers in the variables to be used for cluster analysis? ...
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40 views

How to determine which variables to be used for cluster analysis

I have about 10 variables (features) and want to do cluster analysis of cases (data points). I have a number of ideas about which variables to be included for cluster analysis: Plot the variables ...
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33 views

Looking for a metric to compare clustering solutions to a reference clustering for a large dataset

I am looking for a metric to compare several clustering solutions to a reference clustering that is known to be "correct". Specifically I have a set of millions of genes, and I wish to compare ...
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27 views

Locality Sentive Hashing for Dimentionality Reduction or Feature clustering

So I have read up on LSH and Asymmetric hashing as proposed by Google for their google correlate algorithm. These work by only comparing similar items due to the multiple random hashes, however we are ...
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63 views

What algorithm be best to use for recommendation system based on string features [closed]

I have to build a recommendation engine that will cluster users by their preferences. For example: user that looks for yellow sport GM car should get recommendations for other yellow sports cars. But ...
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13 views

Difference between biclustering and subspace clustering

I have gone through difference between bi-clustering and subspace clustering given here. But is there any difference between them in terms of mathematical definition or are they exactly same as ...
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40 views

Which metric is used in the EM algorithm for GMM training ?

My question concerns the expectation-maximisation algorithm used to estimate the hyper-parameters of a Gaussian mixture model in z multivariate setup. I understand that the EM algorithm uses the ...
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16 views

Segmentation analysis: Correct test to use?

As part of a larger study, we have collected a wealth of data on the interactions customers engage in when buying and using a service. We have tried to look at this relatively close to reality. Hence,...
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19 views

Using centroids to find predictive cluster features

I clustered some data (rows: text documents, columns: word frequencies) using the KMeans implementation in Scikit Learn. This, like most other centroid-based clustering algorithms, returns a centroid ...
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What is maximum and its computation in the function dist() {stats} in R?

In R, we can calculate a distance matrix using the method "maximum" in the function dist() in the stats package. ...
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11 views

Classification of overlapping hetegenerous cell nuclei

We are two people doing a image analysis project on segmentation of cell nuclei. Our data set consist of about 300-400 cell nuclei, from 10-15 images containing different cell types. Our main problem ...
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6 views

Simultaneously Diagonalizable matrices

I'm interested in partitioning matrices into groups which are almost simultaneously diagonalizable. I'm aware that if matrices commute and one of them has no multiple eigenvalues then the matrices are ...
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23 views

features clustering

I'am a bigginner in machine learning so sorry for my basic question. I have a data of persons and for each person i have a list of feature : age, hair-color, skin-color, size, weight, ... I need to do ...
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39 views

Specifying starting values/modes for K-modes Clustering

I have a very large data set with 9000 observations and 25 categorical variables, which I've transformed into binary data and preformed hierarchical clustering and K-modes clustering in R. ...
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56 views

Initializing Fuzzy C means clustering

I have been performing fuzzy c means clustering using Matlab toolbox for my clustering problem. Unfortunately it leads to unstable performance since the selection of parameter membership (Uij) is ...
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37 views

R clustering using mclust: BIC are often NA

I'm working on segmentation/clustering and trying to use Gaussian Mixture Modelling for Model-Based Clustering. I'm using the R package Mclust in order to come up with the best fit for my data. All ...
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14 views

Is the r package “clValid” also applicable for non biological research?

I am trying to cluster a bunch of countries according to certain parameters (GDP, birth rate, etc.). Therefore I am wondering whether I can apply the r package "clValid". From what I got from https://...
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23 views

Clustering, reducing number of levels of categorical variable

I'm dealing with this big dataset which has: 1 categorical variable with 90 levels that represent some sort of "geographical area" 3 continuous variables What I'm trying to do is to "aggregate" ...
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20 views

Checking that partition is not “random” [closed]

Suppose there is a set of objects. Each object has its coordinate on a sphere and one scalar feature. Imagine that someone divides these objects into several non-intersecting subsets. And we have to ...
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Using original centroid as cluster identifier after applying PCA

Take a look at my original data. (masked with purely random alphabetic here) : a b c d e f g h i j A = k l m n o p q r s t u v w x y I'm running ...
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Finding common patterns of activity of time - time series clustering?

I am interested in finding out whether patients attending medical services (e.g. Emergency department; GP surgery) do so in distinct patterns. For instance, some patients may attend at regular ...
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30 views

Question: next step after regression analysis? how to tell if multiple variables all co-correlate?

I am new to regression analysis and I have found that my 'independent variable' or predictor correlates with several dependent variables (through multiple linear regression tests) in a way that ...
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29 views

Data reduction by maintaining data distribution

I have n vectors with m features and also a weight vector with n elements. I'd like to reduce the number of n vectors in a way that the probability distributions of the m (weighted) features (across ...
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Situation that not well represented by hierarchical clustering

The below text is from statistical learning page 394. I highlighted where i stuck. Please help me to understand this. The term hierarchical refers to the fact that clusters obtained by cutting ...
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19 views

Cluster analysis considering uncertainty

Does anyone know how to do cluster analysis that considers the uncertainty (s.e. or confidence intervals in the data?) I want to do cluster analysis on group estimates state-level and regional ...
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42 views

Optics\dbscan produces cluster size smaller than minPts

I'm using optics from dbscan package: ...
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32 views

Help in understanding a clustering technique using neural network

I am having difficulty in understanding a technique for clustering and segmentation of biomedical images using the concept of time series. The paper on which the Question is based is : M. Lacomi et. ...
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76 views

Why not terminating the k-means clustering algorithm after one iteration?

Does anybody know whether there are applications of the k-means algorithm with only one iteration? (Of course, you may feel inclined to not call it k-means anymore in that case.) There is a clear ...
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Feature extraction from data in the form of many manifolds, in hierarchial structure and various dimensions

Is there a known feature extraction method which was developed to cope with data that satisfies the following assumptions?: The data points are real valued vectors in ...
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1answer
19 views

Grouping data in a multiline chart mean + outliers

I have an existing multi-line graph that displays time series data about success percentages of nodes in a cluster in 5 minute intervals, there are more than 50 nodes in the cluster and the way this ...
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1answer
29 views

spectra clustering vs hierarchical clustering

Can anyone please explain that is there any advantage of using hierarchical clustering over spectral clustering? I know how they work but I want to know in which situations its better to use ...
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18 views

How to map data to another feature space

I have some data which is described in a feature space $F$. Let's call this dataset $X_F$. That is, $X_F$ is a matrix where each row an instance and each column is a feature (characteristic). Suppose ...
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26 views

Evaluating kmeans clustering with silhouette coefficient, weird results

I'm performing a kmeans clustering on a 22.000 documents datasets. Not knowing how many clusters I should get, I ran different k values and try to assess the validity of the clusters by determining ...
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55 views

Optimal number of clusters for variables clustering

First of all, I know that this question has been addressed a certain number of times, but I didn't find an answer concerning the clustering of variables, instead of observations. Concretely, I am ...
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37 views

Calculating the adjusted rand index?

I'm really close to understanding the adjusted rand index, but I lack a background in formal maths and I'm struggling to grasp one or two things. I've been using the Wikipedia page primarily. I've ...
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17 views

Calculating internal clustering statistics (Distance Metric)

I have a quick question, which is probably more obvious than I am making it. When calculating internal cluster validation statistics (dunn coefficient, silhouette width), should I always be using ...
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Classifying empirical distributions without ground-truth

I have a big dataset of per-country viewing distributions that I want to cluster. The dataset contains 600,000 elements (I subsample it between 10 and 50 times to prevent swapping), and 242 countries (...
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Using Decision Rules to Make Cluster efect

I have a data set with 3 independent variables and 1 dependent variable. Dependent is play_golf Independents are Humidity, Pending_Chores, Wind I want to create "clusters" of rules and aggregate ...
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58 views

Cluster validation method for no cluster labels and differently sized clusters

I'm primarily a programmer and have little to no training in formal maths or statistics of any kind. I'm working on my dissertation (which foolishly is about clustering data), the process is ...
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74 views

Procedure of clustering seasonality in several time series in R

I want to do cluster analysis of a product monthly sales during 5 years in 30 stores (my data are time series). I want to cluster the stores according to its seasonality. This is an example of my data:...
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37 views

Can I use the Xie-Beni index to validate data transformation parameters in fuzzy c-means clustering?

I am using fuzzy c-means algorithm to cluster my data in various feature spaces and the results differ depending on what kind of transformation I perform on my raw data. I want to know if using the ...
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A question about isoparametric clustering

I am reading this paper by Leo Grady and Eric L. Schwartz on Isoparametric Graph Partitioning: http://cns.bu.edu/~lgrady/grady2006isoperimetric_full.pdf On page 7, directly after equation (15), the ...
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41 views

Unsupervised clustering based on discriminant line

I have quite specific statistical problem, highly limited by its ecological interpretation. I have plenty of "time series" data - I need to link supression of photosythesis to the lack of light (PAR) ...
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45 views

Regression with variable containing multiple entries per observation - clustering right approach?

Setting and Data I would like to run a 2-stage Hurdle regression with various variables describing the funding activity of companies (number of rounds, amount, etc). Some information on the data set: ...
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25 views

How to approach analyzing a dataset of baby speech?

I've been collecting speech data for my baby brother (who is now 6 months old) with the intention of doing computational analysis of the development of his speech patterns. I haven't much deep ...
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K-means with learning proces

I have a data set in which I already know the cluster to which each individual belong just by empirical observation but I want to predict, given the characteristics of a new individual in which ...
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67 views

Log likelihood in EM Algorithm

I try understand the log likelihood in weka. I read about that is a probabilistic metric, but i cant understand, if is better when have low value or high value? How i can get the likelihood value, ...
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4answers
106 views

Deterministic clustering approaches

I need a deterministic [in the sense - robust to the ways of initial input / initial seeds] clustering method to group values in distributions that could be either random, normal or log-normal. ...