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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Clustering Analysis in One Dimension

I have a set of points along an interval. What is the best significance test to measure clustering of the points in the interval (deviation from a uniform distribution)?
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Checking the assumptions of K-means clustering

I want to do a k-means clustering on a dataset containing 22 numerical variables between 0 and 100 and 75 observations using R. I read this post How to understand the drawbacks of K-means on k-means ...
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3answers
35 views

Checking quality of clustering of labeled-class data

I'm performing clustering on a labeled dataset. I would like to check the quality of clustering. Is there a well accepted way of doing that? So basically I would like perform some classification-like ...
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17 views

Comparison of distributions

I measured the velocity of particles depending on some biophysical conditions (summarized data from two DoE plans) for about 100 samples. The goal was to identify the most important parameters ...
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12 views

Clustering Standardized Mortality Ratio

I am bit new to the whole clustering idea. I have a data set that gives information about the SMR in the different states of America from 1995-2000. Hence I want to apply clustering techniques ...
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2answers
21 views

What are some good (and fast) alternatives to dynamic time warping?

I am planning to cluster tens of thousands of time series of different lengths into two groups.
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1answer
19 views

Change in r squared due to clustering in multiple linear regression

Puny undergraduate stats student here. I am examining the effect of two regressors on a predictor. OLS on the raw data (approx 200k cases) yields next to no correlation in the following models: ...
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25 views

Power calculations for proportions, two-stage cluster

I am trying to do power calcs for a survey. It's not an RCT, so I have encountered a dearth of material on this. We are trying to estimate a proportion within a population, and have two stages of ...
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8 views

cross validation for non parametric clustering methods: dimensionality reduction possible?

I do have about 100 data points gathered during a DoE experiment. The response variable was the settling velocity distribution depending on 10 factors. I analysed the 10 % percentile of the ...
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18 views

Spatial clustering based on response

Statistics version: I have a few measurements of a function that takes three inputs and produces a few 2D fields of outputs: f(a,b,c;x,y), with f being a vector of several quantities. I would like to ...
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1answer
23 views

What is the relationship between differential analysis and hierarchial clustering?

I'm currently in an internship for R bioinformatics, where I'm writing software for single-cell RNA sequencing analysis. We're looking for differentially expressed genes between groups, but I don't ...
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10 views

Robust Sparse K Means clusters and valid index

I used the robust sparse k-means for clustering my dataset and I would like to calculate some distance-based statistics for evaluating my results. Should I compute them on the dissimilarity matrix ...
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Algorithms for association rule mining (or alternatives) to “cluster” continuous outputs in supervised settings

I am collaborating with experimentalists who obtained measurements on a continuous scale 0.0 - 1.0, and each sample has ~30 binary features. They basically want to "learn" from this data, for example, ...
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1answer
26 views

Testing Clustering Variables

I have two clusters. Those two clusters were obtained using Fuzzy C-Means with 8 variables. I'd like to know which variables have important role in differentiating the two clusters. Can I use t test ...
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1answer
18 views

Functional clustering with R [closed]

I have a time series data in R, and I am using functional clustering. I would like to interpret a figure that is output below the code. Furthermore, I would like to control line colors and thickness ...
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1answer
36 views

Cluster analysis in bounded data

I have 261 vectors with 9 attributes. Each attributes contains numbers between 0 and 1. I am not sure what the most appropriate clustering method for this kind of data is. Initially, I used the ...
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1answer
36 views

What clustering algorithm should I use for clusters spaced on a grid?

I have some data sets of clusters of points arranged more or less on a regular grid. The data sets have these properties: The data is two, three, or maybe rarely four-dimensional. I know in advance ...
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2answers
37 views

K-means - comparing solutions with SSwithin elbow-method: minimum “too early”

I am running a k-means clustering process in R and I'm comparing cluster partitions of different number of clusters: k = from 1 to 17. Using the elbow-method, I have a minimum at k=5, but this value ...
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29 views

Clustering using gower distance in R [migrated]

I have a dataframe which has categorical and numeric variables. I want to cluster this data using gower distance and get cluster values as a vector as in kmeans function. How can i achieve that?
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How to deal with empty values in a cluster analysis

I'm currently working on my master's thesis. Part of the work is a customer segmentation by means of a cluster analysis. One variable for the cluster determination should be the chronological ...
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28 views

Average linkage clustering

I have a matrix with proximity values $$ \begin{matrix} &1&2&3&4&5\\ 1& 1 & 0.9 & 0.1 & 0.65 & 0.2\\ 2& & 1 & 0.7 & 0.6 ...
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1answer
16 views

If two domains measure the same thing how to approach a cluster analysis?

I would like to perform a cluster analysis on my sample with a set of variables categorized in several domains. This is just fine but my problem is that two domains (one consisting of four and one of ...
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1answer
38 views

Interpret the visualization of k-mean clusters

Following my posted data here, I conducted a k-mean clustering analysis. I refereed to this post: How to produce a pretty plot of the results of k-means cluster analysis? for the clusters ...
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1answer
16 views

Clustering sequence on similarity using percentage identity matrix

I have a set of 400 nucleotide sequences and want to cluster them on basis of similarity. For clustering, I am expecting a similarity <=45% among members of a cluster. Also, there will be a few ...
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1answer
31 views

A non parametric clustering algorithm suitable for high dimensional data

What are suitable clustering algorithms for high dimensional data, where I do not have to input a predetermined number of clusters?
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57 views

Data Preparation for Cluster Analysis

Updated answer to "Data Preparation for Cluster Analysis": Based on the discussions, data normalization and removing correlation among data are often recommended. References posts: 1) Are mean ...
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4answers
316 views

How I can convert distance (Euclidean) to similarity score

I am using $k$ means clustering to cluster speaker voices. When I compare an utterance with clustered speaker data I get (Euclidean distance-based) average distortion. This distance can be in range of ...
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2answers
56 views

K-means: Why minimizing WCSS is maximizing Distance between clusters?

From a conceptual and algorithmic standpoint, I understand how K-means works. However, from a mathematical standpoint, I don't understand why minimizing the WCSS (within-cluster sums of squares) will ...
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how to cut Dendrogram using linkage distance and how to read it?

i tried to make clusters of monthly rainfall data over my studied area. i found it pretty difficult as to determine how many cluster i should have since i am new in statistics. from my linkage ...
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Dig deeper on “Determine the Number of Clusters and Validate It”

Updates to this thread: Based on Anony-Mousse's comments on my current results, there is only one big cluster in my data set. However, I think it might still be possible to reveal the clusters if I ...
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3answers
93 views

How to find the line?

Today I faced what I think is a very simple problem, but could't solve. I have this plot (data is below) with(mydata, plot(x, y)) It's clear that there are ...
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1answer
22 views

Incorporating new words in tfidf feature-vector for online clustering

I am building an Online news clustering system using Lucene and Mahout libraries in java. I intend to use vector space model and tfidf weights for Kmeans(or fuzzy/streamKmeans). My plan is : Cluster ...
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1answer
25 views

PSO Clustering using R using Repplab package

I wish to try clustering a matrix of numerical data using swarm intelligence. (Matrix is 28000 X 53 and sparse). I'm working in R and found the REPPlab package and used the EPPlab function. My ...
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1answer
20 views

Complement learning

First off, complement learning is a term I made up, not sure if it really exists. Given that the ground truth consists of 2 classes: class 1, class 2, and also two observed sets: oset 1, oset 2, such ...
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36 views

Supervised clustering/classification in a streaming environment

I am faced with a challenging problem and I was wondering whether someone could point me in the right direction of existing research literature. The problem is the following: Given a stream of data ...
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2answers
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Finding cluster number based on distance & max element count

Given two constraints: The maximum distance d an element can lie from a cluster centroid (or medoid) The maximum number of elements n in one cluster Is it possible to find the minimum number of ...
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Clustering before or after ordination

Can someone explain the implications of performing clustering either before or after performing NMDS? I have some ecological data and I am performing a clustering analysis to identify communities of ...
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1answer
55 views

Measure the similarty between two sequences of letters

I'm trying to measure the similarity between two time-series sequences of letters with different lengths (e.g. s1=[A;A;A;C;B], s1=[Q;A;A;A;A;A] ). The order is very important. (e.g. s3=[A;A;A;C;C;C;C] ...
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1answer
58 views

Case-control Matched Clustering in Generalized Estimation Equation (GEE) (R:geeglm)

Question: I have matched case-control data and I would like to take advantage of that in my GEE analysis. In the standard approach to GEE analysis, we call each subject a cluster and fit ...
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What is second eigenvalue?

I am trying to understand Proc Varclus. This page says "2.If the second eigenvalue for the cluster is greater than the specified cutoff, then the inital cluster is split into two clusters." What is ...
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13 views

Difference between PROC VARCLUS and factor analysis

I understand factor analysis and hierachical clustering well but PROC VARCLUS is new to me. I read in this paper that PROC VARCLUS is a combination of Factor analysis and Hierachical clustering. Can ...
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0answers
17 views

Cluster of Cluster analysis across correlated longitudinal data

I am intrigued by the Cluster-of-Clusters approach (implemented via the bioconductor package ConsensusClusterPlus) and would like to apply it to my data matrix. However, I am not sure how appropriate ...
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37 views

Affinity Propagation (sklearn) - strange behavior

Trying to use affinity propagation for a simple clustering task: ...
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30 views

analysis of change and clustering

I want to do an analysis of change over two time points for a sample of children who move from primary to secondary school. Some children will move home, but all have moved school. Predictors: home ...
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3answers
29 views

Cluster similarity matrix as energies

I have a symmetric score matrix and I would like to cluster the values in two dimensions rather than through a tree. Is there any method / library that would take the input matrix and treat the scores ...
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2answers
24 views

Matrix clustering based on a Jaccard distance cutoff

I'm trying to figure out how to group elements of a binary matrix based on a given Jaccard distance cutoff. For example, suppose that I have information on the types of food carried by various grocery ...
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13 views

Statistical test for cluster independence?

1) If I want to test whether the cluster in red at the bottom figure here is a statistically separate cluster from nearby ones, what do I use? MANOVA? Anything else? 2) Any suggestions how to ...
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Statistical distances and time series of distributions clustering

I am interested in clustering $N$ time series of $T$ 'values' each. These values are distributions (which can be represented by their cumulative distribution functions (cdf), or their probability ...
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28 views

mean square distortion of quantization data set

I am using the matlab function lloyds to cluster a 1-dimensional timeseries. [partition,codebook,distor] = lloyds(training_set,initcodebook); and I get that the ...
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12 views

Representing clustered sequences in PCoA

I'd like to represent a set of clustered dna sequences (at a 0.0049 threshold) under a PCoA. But I have to calculate a distance matrix once the clustering done. How could I do that since the result ...