Questions tagged [model-based-clustering]

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Optimality of KL-Divergence for Clustering Distributions

I have two related theory questions. In both cases, I imagine the following workflow: I see several datasets $D_{1},\ldots,D_{k}$, I transform these observations into estimated distributions $\mu_{1},...
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Justifying choice of number of clusters using Mclust

I am attempting to justify my choice for the number of clusters in a model I am running using Mclust. The output from Mclust indicates that the optimal number of clusters is 17. By studying the output ...
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K-Means clustering technique for monthly data

I have an Unsupervised problem where user's Credit Card payment data is given for each month for various users for one year. One of the feature in the data having "User Id". For most of the ...
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How to cluster Multiple variables (11 numerical variables ) together into different buckets?

what's the best way to bucket multiple variables together? Below is my data which has 11 numerical variable. I tried with the maximum is two variable clustering and grouped them based on the clusters.....
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EM algorithm for multivariate gaussian with diagonal covariance matrix

Ok so quick question. Say I need to use the EM-algorithm to estimate the parameters of a multivariate gaussian $$ f_{k}\left(x ; \theta_{k}\right)=\frac{1}{(2 \pi)^{P / 2}|V|} \exp \left(-\frac{1}{2}\...
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Which type of cluster analysis to perform?

I am trying to explain variability in the outcome, and understand factors that may be associated with different clusters? I am confused as to which clustering method to use to obtain 3 clusters as ...
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Do Gaussian Mixture Models monotonically decrease the sum of squared distances when number of clusters increases?

I am comparing the clustering performance of two closely related machine learning methods: K-means and Gaussian Mixture Models (GMM). Part of this research is selecting the best number of clusters K. ...
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Understanding and implementing the last step in the 3-Step Latent Class Analysis using covariates from Vermunt 2010

I am interested in implementing the 3-Step approach for LCA with covariates ($Z_i$) in R. According to Vermunt (2010), the "Standard" three-step approach would involve (mentioned in pages 5 ...
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How to make inference on cluster-specific parameters in a Bayesian mixture model

Suppose I have a mixture model, for example of the kind $$ y_i \mid w, \{\theta_h\}, H \sim \sum_{h=1}^H w_h f(y_i \mid \theta_h) \\ P(H=h) = q_h \\ w \mid H \sim Dirichlet(\alpha) \\ \theta_1, \ldots,...
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Identifying inflexion point in elbow method (cluster analysis)

I am looking for the optimal number of clusters to conduct a cluster analysis and used the following code to determine it: ...
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Clustering Highly Skewed and Segmented Data

So I am trying to cluster a dataset that looks like the following: I have tried K-Means and GMM, which give me horrible results. I have tried DBSCAN, which was okay, but it is difficult to choose the ...
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Can clustering with Gaussian mixture models be done based on cosine similarity?

Apologies if this has already been answered; I found some similar posts (here and here) but don't feel they answered the specific question I have. Please feel free to correct any misunderstandings in ...
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What is the interpretation of the weights in the GMM?

GMM is $p(x|\theta) = w_1 \mathcal{N}(x|\mu_1,\,\sigma_1^{2})\ + w_2 \mathcal{N}(x|\mu_2,\,\sigma_2^{2}) + w_3 \mathcal{N}(x|\mu_3,\,\sigma_3^{2})\,$ What is the interpretation of the weights here? Do ...
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Looking for clues on a possible method or approach for clustering particle data in the form of pulse shapes

I'm a biologist by origin, and I'm asking this question to the math community to learn from the vast knowledge that I don't posses myself but is out there in the math field. Edit: This question was ...
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Clustering Algorithm for for Different types of dimension

I want to cluster radar data but using its position (x,y) and its radial velocity. As position parameters have same units (meter) but radial velocity is in m/s. Which algorithm can be used for such ...
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Multi variable clustering cartographical data

Firstly , my knowledge in statistics is very limited , so excuse me if I'm ask a none well placed question. I have a country ,( example : USA ) , and i have 3 set of data 1) position (lat , lng ) ...
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Multivariate mixture models

I am new to mixture modeling and have successfully used bernoulli mixture models to cluster datasets of binary data. My real purpose, though is to cluster datasets with mixed data types: normal, ...
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Clustering of temperature and precipitation courses. Searching for approach

I would like to cluster not only single observations, but I would like to cluster all observations for temperature together as a temperature course. So the goal is to cluster the temperature courses. ...
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1 answer
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How to explore high dimensional data to inform a choice of clustering method?

I want to cluster users of a web app based on their engagement, my data looks approximately like: id | count of action 1 | count of action 2 | ... | count of action n I have 40 different counts and ...
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In cluster analysis, how to determine if a variable has impact on the clustering process?

I am using model-based clustering to split a sample into 4 clusters, and would like to know if gender is a determining factor for the clustering of this sample. My attempt was to compute the in-...
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2 votes
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Community Detection for Complete Weighted Network [duplicate]

I am wondering if someone who has experience in trying to perform community detection algorithm with complete graph with weighted network. As weighted networks represents the similarity of each node ...
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4 votes
1 answer
567 views

Mclust: Data frame order affects solution

I've come across some behavior in mclust::Mclust that I would not have expected, which is that the order of variables in the data passed to ...
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Multiple correspondence analysis for clustering (unsupervised learning) [closed]

I have limited stat/coding knowledge yet I try to do user clustering using unsupervised method using R. I have about 2795 observations gained from survey (mixture of categorical and scale questions). ...
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3 votes
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Mixture probabilistic model on mixed data

When dealing with homogeneous types of data, we can employ mixtures of gaussians (for continous) or some kind of k-proptotyping (ordinal-nominal). I am investigating around the statistical/machine ...
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1 vote
1 answer
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Fit indices using MCLUST latent cluster analysis

I conducted latent class/cluster analysis in R using the package MCLUST. I have a revise and resubmit for my paper, and the reviewer suggested making a table of the fit indices for the cluster ...
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Merging the results of soft-clustering algorithm

The established soft-clustering algorithms like Fuzzy-k-means (Wikipedia), Gustafson-Kessel, Gath-Geva for point wise data or the funclust algorithm in functional data context are random-operating ...
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1 answer
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Clustering unrelated (with no correlation) data

The objective of clustering analysis is to group data with similar characteristics in clusters, but in this case, I want to find the most unrelated data to group into clusters. In my particular case, ...
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13 votes
1 answer
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Mclust model selection

The R package mclust uses BIC as a criteria for cluster model selection. From my understanding, a model with the lowest BIC should be selected over other models (if ...
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2 answers
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Problem in a cluster analysis of User behavior

Data set that extracted from Log file, the simplest way to represent it is by use User- Page view matrix which represent each user how many time visit corresponding page as attached in sample image, ...
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1 vote
1 answer
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How to differentiate two distinct linear populations with clustering in R

I am new to clustering. My apology if this has been asked before. I'd like to differentiate two distinct linear populations within sample matrix, and tag them differently. Apparently k-means couldn'...
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Stability of clusters/mixtures from GMMs

Some background I have a data set with around 2000 samples and 16 features. Me and my colleague are trying out different methods for clustering and currently we are converging to the usage of a ...
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1 vote
1 answer
548 views

Best Clustering Technique for Probability Scores

I have a data which which have 17 variables i.e. 17-Dimension data. The Data is a result of Max-Diff exercise which is performed for ranking these 17 attributes and have comparative preference/...
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3 answers
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Clustering of distributions in R

I have a set of distributions corresponding to predictions for how each of hundreds of players will perform. I am looking to identify the distinct distributions of players. In other words, I'm ...
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3 votes
4 answers
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Clustering methods ⊂ Unsupervised learning

Is it proper to say that clustering methods are mostly unsupervised learning techniques, with some exceptions such as model-based clustering?
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Clustering based on distance measure violating triangle inequality

Suppose I have a set of categorical data $X=\{x_1,x_2,\cdots, x_n\}$, (in my case $n =~ 10,000-50,000$) as well as a precomputed "distance" measure $g(x_i,x_j)$ (in my case I just have an array of ...
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2 votes
1 answer
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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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1 vote
1 answer
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Feature selection in clustering

I am looking for a method for feature selection in Gaussian Mixture Models. I have a dataset with 2000 records and 40 variables. I tried to use the "clustvarsel" package in R, which use the BIC as ...
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2 votes
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186 views

Stochastic Block Model Priors

In the generic stochastic block model (binary edge data, no degree correction, etc.), if an uninformed prior is used for the Bernoulli coefficients i.e. Beta with $(a,b) = (1,1)$, will the model ...
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Consensus methods for interpreting results of a cluster analysis

With cluster analysis, sometimes we want to assign meaning to the nature of the identified clusters. This is subjective and often done by a single person (or very few people) with perhaps some ...
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5 votes
1 answer
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Best clustering algorithm for real estate data

I want to cluster real estate data to determine average price patterns in city and rural regions. My data set contains size, number of dorms, bathrooms and coordinates of the properties. Which would ...
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2 votes
1 answer
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Unnatural clustering with known clusters shapes and optimization criteria

My question is similar to this question Clustering with shape prior, but with additional information. The second answer suggests a mixture model approach to this problem, which is something like ...
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480 views

How the quality of clusters made in SPSS can be evaluated?

How the quality of clusters made in SPSS with the method "TwoStep clustering" can be evaluated? Which test should be applied to be sure that the quality is good.
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2 answers
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What are Clustering techniques for this case? [duplicate]

What type of clustering methods are available for ordinal, nominal and ratio variables? Suppose I have one ordinal, one nominal and one ratio variable; is there a common clustering technique that can ...
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0 votes
1 answer
410 views

R codes for variation of information criterion using "mclust"

I am developing model-based clustering. First, I developed model-based clustering in R using "mclust." Next, I wanted to take 75% of the sample, re-run model-based clustering and compare the ...
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3 votes
2 answers
1k views

Create bins for lognormal data for cluster analysis

I have a series of dollar amounts that are highly right skewed, but are roughly log-normal. I want to put this grouped dollar amount as a predictor variable into a latent class cluster analysis. In ...
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5 votes
2 answers
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LCA number of parameters & degrees of freedom

I have a series of physicians' claims submissions. I would like to perform cluster analysis as an exploratory tool to find patterns in how physicians bill based on things like Revenue Codes, Procedure ...
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Clustering groups that have replicated measures: hierarchical clustering on group-average VS regression tree

I measured 2 continous dependent variables (V1 and V2) on 10 occasions (10 replicates) for each of 4 groups. I aim to cluster my groups. i.e. I dont want to cluster replicates, since this could mix ...
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4 votes
1 answer
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Ratio estimation model in 2-stage cluster sampling

I've been reading about stratified sampling, 2-stage SRS sampling, and ratio estimation in finite populations and I have a question. When the ratio estimator is introduced, it seems that in order for ...
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3 votes
1 answer
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Estimating effects on membership in a cluster

Suppose you want to find clusters based on a set of variables $Y$, and that you want to estimate the effects of some variables $X$ on membership in those clusters. Here is how I am doing it now. Step ...
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5 votes
2 answers
2k views

Are there any good papers comparing different philosophical views of cluster analysis?

Lots of people use cluster analysis. I've heard very few explicitly say why. I imagine this is because within a given field, most researchers seem to understand why clustering is used for the problems ...
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