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Questions tagged [model-based-clustering]

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cluster uncertainty, silhoutte coeffs and classification accuracy from DFA. How are these related?

I am slightly confused by some of the results I am getting from model based cluster analyses (mclust in R), calculating silhouette coefficients (silhouettes in R based on euclidian distances) for ...
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2answers
26 views

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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1answer
25 views

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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11 views

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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Guassian Mixture Classification: interpretating component x variable means matrix

The Guassian Mixture model output by mclust::Mclust() function has a $parameters$mean element which is a matrix with dimensions ...
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17 views

Group comparison after clustering (without using statistical tests)

I have a dataset whose variables can be grouped in variable sets (VS) 1 and 2. VS1 represents blood parameters, VS2 other phenotypic data. Variables in VS1 are standardized to N(0,1). I have ...
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24 views

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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117 views

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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1answer
69 views

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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77 views

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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18 views

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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1answer
260 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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1answer
143 views

Multiple correspondence analysis for clustering (unsupervised learning)

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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93 views

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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1answer
772 views

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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1answer
39 views

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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1answer
235 views

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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1answer
5k views

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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2answers
900 views

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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1answer
55 views

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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1answer
310 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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3answers
755 views

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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4answers
173 views

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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199 views

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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1answer
316 views

Predicting cluster probabilities/ cluster membership for new cases from Mplus output

I used Mplus to perform a latent class analyses/finite mixture analyses with categorical and continuous indicator variables. I obtained a well defined 5 cluster solution. I would like now to predict ...
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1answer
798 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
170 views

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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0answers
158 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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0answers
96 views

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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1answer
230 views

Confirmatory latent variable cluster analysis with mplus

I would like to do a confirmatory latent class cluster analyses (finite mixtures) with a continuous and several categorical variables. I know how I can constrain binary variables (such as Cluster A ...
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1answer
2k views

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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1answer
88 views

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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0answers
427 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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2answers
110 views

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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1answer
300 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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2answers
790 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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2answers
2k views

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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149 views

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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1answer
424 views

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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1answer
125 views

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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2answers
980 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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1k views

Why does some model-based clustering fail to fit with a large number of dimensions?

I am attempting to cluster data using Mclust. The data is originally from a dissimilarity matrix, transformed via multidimensional scaling in R (MASS::isoMDS). As I ...
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1answer
755 views

Implementing EM clustering for a mixture markov model

I have a mixture Markov model (containing K clusters, or components) that I am trying to train, e.g perform clustering over a set of varying length sequences. Each component of the model is a first ...
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1answer
305 views

Can first-order Markov chain be considered a special case of a hidden Markov model?

I am trying to apply R depmixS4 package in order to cluster time series with model based clustering. The model consists of K components, each being a first order Markov models. The Expectation-...
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2answers
8k views

Cluster analysis on ordinal data (Likert scale)

I want to do clustering of my data in R, using kmeans or hclust (I am a new R user). My data is ordinal, Likert scale, to measure the causes of cost escalation. I have 41 causes "variables" that ...
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2answers
2k views

Cluster clickstream data

I've recently entered the realm of machine learning and a project I am working on requires me to cluster users based on the order they visited webpages on a website. I have data in the form of: ...
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1answer
2k views

What are the primary differences between Taxometric analyses (e.g., MAXCOV, MAXEIG) and Latent Class analyses?

Recent research has attempted to determine if certain psychological constructs are latently dimensional or taxonic (i.e., including taxons or classes). For example, researchers may be interested in ...
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1answer
1k views

How to convert molecular categorical variables to dummy variables for cluster analysis?

I would like to use a clustering method, e.g. 'mclust', in R to classify each individual in my dataset to k groups. I have 7 continuous and 3 categorical variables. These and other hierarchical ...
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1answer
2k views

Looking for a hierarchical-clustering method for multiple data types

I would like to find a hierarchical-clustering method useful to assign a group membership into k groups for all individuals in my dataset. I have considered several classic ordination methods, PCA, ...