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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30 views

Comparing two graphs/markov chains by comparing their clusters

I have an undirected graph representation of my system (a dynamical system), i.e. I have some labelled nodes and bi-directional edge weights, so everything is in a Markov matrix form. Now I can form ...
0
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0answers
18 views

Dealing with nuisance parameters in a cluster wild bootstrap

I'm conducting inference on a regression parameter using a wild cluster bootstrap percentile-t procedure, imposing the null hypothesis, where my weights are six-point weights as described in Webb: ...
0
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0answers
18 views

Cluster logistic regression datasets

Let's say that I've got a 100 advertising campaigns and for each I'm trying to predict that a user will click on the advertisement or not using logistic regression. So basically I'm creating 100 ...
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2answers
30 views

Clustering or other mechanisms for implementing generic spam detection

In normal case I had tried out naive bayes and linear SVM earlier to classify data related to certain specific type of comments related to some page where I had access to training data manually ...
1
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1answer
21 views

Interpretation of LSI/LSA when reducing the number of documents

Usually LSI/LSA is done on a TermFrequency matrix (each row a document, each column a term) to reduce the dimensionality along the terms dimension (i.e. there are too many words). In that way we would ...
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4answers
143 views

Determine the number of clusters for K-means automatically

Since a couple of days I research for a method to determine the number of clusters for K-means automatically, I found elbow method but I can not till now understand its principle. Is there any ...
0
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0answers
20 views

Two Step Cluster Analysis with categorical variables [duplicate]

Can I use two step cluster analysis if I have only either continuous or categorical variables? I understand it can deal with a mixture, but I don't know if it is suitable to use for just one type. ...
0
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0answers
41 views

How to plot SSE with R's hclust

I ran a hierarchical clustering fit with the ward.D2 option in R's hclust function. My understanding is that then the distance ...
1
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1answer
78 views

My MCMC do not overlap : Mixturemodel with JAGS and R

I fitted a JAGS model and I have those results : My questions are: Why do my chains not overlap, and how can I fix that? I used the following method: My model is a mixture Gaussian model of ...
2
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1answer
84 views

CART for unsupervised learning - clustering

I recently met some guys that employed CART (Classification and Regression Trees) for unsupervised learning. In particular for clustering. The idea is very simple: Make a copy of the original ...
2
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0answers
21 views

Are there any statistical measures to determine how “clustered” a dataset is? [duplicate]

I have two datasets that I'm trying to compare. In one dataset, the points appear to be pretty uniformly distributed. In the second dataset, they appear to somewhat more clustered - i.e. there ...
2
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1answer
60 views

Does it make sense to conduct cluster analysis with single variables as well as a variables derived from multiple items?

As part of my research I wonder whether it would be OK to conduct a cluster analysis with variables derived from a multiple item construct, as well as single variables. The objective is to segment ...
3
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2answers
153 views

Feature selection for clustering problems

I am trying to make group together different datasets using unsupervised algorithms (clustering). The problem is that I have many features (~500) and a small amount of cases (200-300). So far I used ...
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0answers
21 views

Preprocess data before classification [duplicate]

Let's say that my training samples are extracted from multiple sources, each of which produces a bunch of samples. Samples produced by the same source are highly correlated, and relatively much more ...
0
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1answer
30 views

Selecting features to find predefined groups in clustering

I have a dataset I believe is easily clustered into a few groups, however, a bunch of junk features interfere with clustering. Is there a method of eliminating these bad features within this dataset? ...
12
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1answer
177 views

(Why) Has Kohonen-style SOM fallen out of favor?

As far as I can tell, Kohonen-style SOMs had a peak back around 2005 and haven't seen as much favor recently. I haven't found any paper that says that SOMs have been subsumed by another method, or ...
5
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3answers
129 views

Graph clustering algorithms which consider negative weights

I have a graph instance with weighted directed edges which values can be in range [-1,1]. I need to do clustering on this graph, in order to find out groups in which vertices are more correlated. I ...
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2answers
45 views

Is it possible to combine classification and clustering?

I am working on a research to detect ssh bruteforce attack using data mining. I would like to using ip geolocation as one of attributes. But, ip geolocation can't be used in classification algorithm ...
0
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0answers
31 views

Using clustering for attribute discretization

I have a dataset where I need to explore using unsupervised technics (clustering and association rules). What are the best strategies to discretize the numeric attributes? Also, does this (attribute ...
0
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1answer
31 views

K-means clustering matrix - normalized values

I have to perform pairwise correlations and clustering on the rows of a matrix like the following: ...
0
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1answer
21 views

Standardize or not standardize before clustering [duplicate]

Objects in my sample have multiple dimensions. Some dimensions are measured in kilometers and some in kilograms, there are also categorical variables that I need to quantify. I am planning to use ...
0
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1answer
16 views

Avoiding cluster recalculation in large scale clustering

I am working with a large dataset containing about 500 million records and about 50 discrete dimensions. I am planning to cluster these records into a number of distinct clusters (~30). Now, every ...
0
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0answers
28 views

Fuzzy Clustering Evaluation Metrics

I have a corpus of text documents which I am clustering using LDA & C-Means. I am trying to find the best input for the LDA algorithm (stemming, stop words removed etc), and I want to evaluate the ...
2
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0answers
44 views

Separation of points clouds via classification methods

I have multiple images from a 3D-Scanner in point cloud form. Part of the image is a fixture to hold the object to be scanned. I want to extract the object itself by classifying the fixture and the ...
1
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1answer
36 views

Clustering data with Fourier series representation

We are analyzing temporal behavioral patterns across many users and we want to cluster users in order to understand "natural types of behavior". Our idea is to represent the data (672 bins for each ...
0
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1answer
43 views

Hierarchical clustering on large data set. Practical example

I have a dataset with 120k rows each one representing a job and I can have as many as 200 columns (these are the skills required to complete the job). S_ij=1 if the jth skill is required to complete ...
1
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2answers
18 views

Consistent cluster labels after several runs of algorithm

When running a clustering algorithm several times (e.g. k-means) I get different assignment of labels for the same clusters (that is understandable since labels are just symbolic). Is it possible to ...
2
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0answers
33 views

Appropriate distance measure

I'm working with a dataset containing 600 matrices (dim: 44x3) with numerical results of applied tests (pass, fail, toVerify). Data is organized in rows. Row nr 1 represents test nr 1. Tests can be ...
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1answer
55 views

Clustering related areas with k-means in WEKA

I am trying to cluster related areas of knowledge. A sample of my file is: ...
0
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0answers
43 views

Text Clustering - Extracting meaningful title / description from the clusters generated

I use k-means algorithm to cluster my data(multiple reviews of an app). I need to generate meaningful sentences which will describe each of the cluster. One approach that I tried was to find the data ...
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1answer
79 views

dtw(distance.only = TRUE, …) : No warping path exists that is allowed by costraints [closed]

Using the UCR time-series database and modification in this code: ...
0
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1answer
40 views

Measures for Clustering Validations [duplicate]

I have unlabeled dataset and I'm using the hierarchical clustering to generate a groups from this data. I had a look to the lit and I found that there are two approaches to evaluate the clustering ...
3
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0answers
52 views

Reconciling wildly different $\chi^2$ independence test results (bootstrap clustering)

I have some data that should be randomly assigned to treatment $T$, and am running some tests on observables to give evidence that this is indeed the case. Let's focus on an outcome I'll call $X$, ...
2
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1answer
95 views

Advice for clustering a tricky data set

I have a set of data with about 15,000 vectors which fall into three classes all with the same number of vectors. Some of the data is categorical and some numerical so I am using ...
4
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1answer
155 views

When to use LDA over GMM for clustering?

I have a dataset containing user activity with 168 dimensions, where I want to extract clusters using unsupervised learning. It is not obvious to me whether to use a topic modelling approach in Latent ...
1
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0answers
41 views

Alternative Optimization, Picard Iterations and Fuzzy C-Means (FCM) objective function

Question In Bezdek's [1] treatment of FCM (details below) after setting up the model and explaining you can't solve it directly/with usual gradient methods, he then says he uses Picard's method to ...
5
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2answers
400 views

How to plot clusters in more than 3 dimensions?

I have 100 data points, observed on 15 variables. I want to cluster my 100 observations, but I am unable to visualise 15-dimensional clusters in MATLAB.
0
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0answers
23 views

Clustering variables by dependence

Let consider a set of $p$ variables. I have a sample of size $n$ of these. I would like to determine groups of variables that depends on one another. My current idea is to use distance correlation as ...
0
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1answer
19 views

Comparing/Mapping K-means Cluster Centers Month-by-month

A colleague of mine has some monthly data that they've normalized using Z-score. So, each month, the data is normalized relative to the mean and stddev of that month and K-means is performed (K = 10). ...
0
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1answer
16 views

Clustering Evaluation Assumption

I have been reading up on some clustering evaluation techniques in this Stanford NLP textbook On page 359, it defines each of TP, TN, FP & FN. I am having trbouel understanding why the definition ...
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0answers
14 views

Heteroskedasticity in complex equations

I am running a logistic regression on about 30.000 cases, clustered by Countries and weighted (iweight) by relative importance (nonintegers) in Stata. The rvfplot command does not work (logit) and ...
0
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0answers
20 views

cluster validation PBM scores

I am using the PBM scores as defined in the paper "Validity index for crisp and fuzzy clusters". According to the paper PBM score is defined as $PBM(K)=\left(\frac{1}{K} \times \frac{E_1}{E_K} ...
3
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1answer
130 views

Clustering: Do I have to transform all variables derived from a single categorical variable in the same way?

Basic problem Here is my basic problem: I am trying to cluster a dataset containing some very skewed variables. The variables contain many zeros and are therefore not very informative for my ...
1
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0answers
19 views

unified estimation of discrete Markov Model

Background I have a multivariate dataset, say M x N, where M is the number of variables and N is the number of samples. Now, the pattern of dependencies between the M variables changes across the N ...
0
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2answers
43 views

Clusterization a Dataset by Category of Another

I have limited knowledge about Machine Learning unfortunately and I want to clusterize a dataset with attributes of another. I have two different data sets which are users and books. Users have ...
0
votes
1answer
46 views

Interpreting hierachchical cluster output

This is a dendrogram resulting from a hierarchical clustering using SPSS. I thought the clustering is done in the following way. I would like to know if the way I am interpreting is correct. ...
8
votes
1answer
174 views

Clustering — Intuition behind Kleinberg's Impossibility Theorem

I've been thinking about writing a blog post on this interesting analysis by Kleinberg (2002) that explores the difficulty of clustering. Kleinberg outlines three seemingly intuitive desiderata for a ...
1
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1answer
43 views

TSS returned by K means clustering is always the same

I have high dimensional ($m \approx 2k$), high sample (n=140,000) dataset in R that I load into memory run PCA on it (returns $m \approx 400$ components to cover 95% of variance) then I run k means ...
0
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1answer
20 views

Derive conditions on features from clustering

disclaimer: I'm a noob. So bear with me because I don't even know the right terms to search waht I'm looking for. I have this problem: I do cluster a dataset with all numeric features. I want to ...
1
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0answers
15 views

mixture of 2 Gaussians and using a priori information about one of the Gaussians

I am working on a large dataset of 2 populations, one is healthy controls and other is considered to be dysfunctional My variables interests suggest a good fit for a unitary Gaussian distribution for ...