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Choosing number of classes in LCA

I'm an undergrad student, a little confused about goodness of fit tests. I'm trying to choose the appropriate number of classes for a latent class analysis using ...
dancing_monkeys's user avatar
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9 views

What are the right metrics to validate the performance of a custom clustering model with three possible outcomes?

I have developed a custom clustering model on top of MiniBatchKmeans, that has three possible outcomes for each data point: Assign the point to the correct cluster. Assign the point to the wrong ...
Sanjay Mythili's user avatar
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20 views

Understanding assumptions of equivalence of random effects variances; what to do when violated?

The random effects model is stated as: $Y_{ij} = \mu + \tau_i+\epsilon_{ij}$ Where, $\tau_i \overset{iid}{\sim} \mathcal{N} (0, \sigma^2_{\mu} ) \\ $ $\epsilon_{ij} \overset{iid}{\sim} \mathcal{N} (0, ...
Estimate the estimators's user avatar
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95 views

Expectation Maximization on Multivariate Gaussian Mixture Model for clustering

I have a dataset with 1000 observations and two features that define those N=1000 data points. Hence it is 1000*2 input matrix. I need to cluster them into k clusters. I am not understanding the E-M ...
Oindri's user avatar
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9 views

Criterion to assign individuals to clusters in bayesian mixed model with distribution of probabilities

I have a dataset with a set of individuals indexed by $i = \{ 1, ..., N \}$, and I make a number of measuremenets under two conditions for each individual to measure the effect $\beta$ of my ...
dherrera's user avatar
  • 1,268
1 vote
1 answer
29 views

Cluster uncertainty in Linear Regression

Is it possible to introduce cluster probabilities into a regression? Consider the Old Faithful Geyser data set. Most clustering algorithms find 2 clusters when analysing eruption times and waiting ...
29703461's user avatar
2 votes
1 answer
82 views

PCA : how to cluster data to differenciate my data the most while considering their groups

I have to do a PCA in R for a project, but I have 300 data in 15 differents groups, and I want to find the reduced space which gives me the most variability between the groups and cluster my data in ...
Marguerite's user avatar
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1 answer
105 views

Model based clustering equivalent to K means?

Is it OK to say something like this: "A model-based clustering with a hard threshold is equivalent to a k means clustering"? One of my instructors stated this in his slides, I kind of doubt ...
Zhili Qiao's user avatar
1 vote
0 answers
40 views

Loss function definiton for relabelling

Taken from the appendix to the paper (Yongning Wang & Ruey S. Tsay) of this (2019) paper Clustering Multiple Time Series with Structural Breaks. Appendix to be downloaded her Appendix To fix label ...
user773674's user avatar
1 vote
0 answers
127 views

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 ...
Archaeolexicologist's user avatar
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566 views

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}\...
Susan-l3p's user avatar
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34 views

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 ...
user13514792's user avatar
1 vote
0 answers
96 views

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. ...
Rinze Bloem's user avatar
1 vote
0 answers
472 views

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 ...
srikanth's user avatar
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47 views

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,...
mariob6's user avatar
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584 views

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: ...
Catarina Toscano's user avatar
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193 views

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 ...
The Dude's user avatar
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4 votes
0 answers
702 views

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 ...
phamilton's user avatar
1 vote
2 answers
2k views

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 ...
floyd's user avatar
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2 answers
33 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 ...
Mark's user avatar
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1 answer
33 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 ...
TonyParker's user avatar
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0 answers
18 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 ) ...
MoxGeek's user avatar
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3 votes
1 answer
158 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, ...
Zelazny7's user avatar
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1 vote
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162 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. ...
G. Sozu's user avatar
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1 vote
1 answer
143 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 ...
František Kaláb's user avatar
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0 answers
621 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-...
shavendy's user avatar
2 votes
0 answers
32 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 ...
Billy LPL's user avatar
4 votes
1 answer
783 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 ...
Cody's user avatar
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0 votes
1 answer
538 views

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). ...
tmhs's user avatar
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3 votes
0 answers
170 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 ...
Guillermo González Sánchez's user avatar
1 vote
2 answers
2k 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 ...
jamie's user avatar
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0 votes
1 answer
216 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 ...
Jonas's user avatar
  • 31
1 vote
1 answer
851 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, ...
Manuel's user avatar
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14 votes
1 answer
11k 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 ...
Jon's user avatar
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0 votes
2 answers
1k 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, ...
Ray ben 's user avatar
1 vote
1 answer
59 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'...
Jin's user avatar
  • 11
1 vote
0 answers
63 views

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 ...
Gumeo's user avatar
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1 vote
1 answer
630 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/...
Dileep Vishwakarma's user avatar
1 vote
3 answers
2k 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 ...
itpetersen's user avatar
3 votes
4 answers
227 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?
Pippo's user avatar
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1 vote
0 answers
806 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 ...
Benjamin Horowitz's user avatar
2 votes
1 answer
1k 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 ...
Bade's user avatar
  • 121
1 vote
1 answer
266 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 ...
Fabio's user avatar
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2 votes
0 answers
204 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 ...
Dan's user avatar
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1 vote
0 answers
112 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 ...
D L Dahly's user avatar
  • 3,763
5 votes
1 answer
3k 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 ...
R.D's user avatar
  • 195
2 votes
1 answer
141 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 ...
NGInd's user avatar
  • 75
0 votes
0 answers
535 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.
Alexey's user avatar
  • 101
-1 votes
2 answers
139 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 ...
learner's user avatar
0 votes
1 answer
446 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 ...
user3731653's user avatar