Questions tagged [clustering]

Cluster analysis is the task of 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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7 views

Is there any method for analyzing the convexity of a density-based cluster? [on hold]

I was looking for a method which can define the convexity status of a density-based cluster. I mean a method which gets the points of a cluster and maybe some parameters as its input, and for the ...
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15 views

Comparing clusterings of different spaces

I have developed a graph embedding method that learns feature representations for each node in the graph based on the graph topology. I want to demonstrate that the learned feature vectors yield ...
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1answer
26 views

Is there way for clustering joined rectangles by thickness? [on hold]

Here is an example dots representing coordinates of pixels added more representative example
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11 views

Minimum N size for HDBSCAN / DBSCAN [on hold]

I have read here that small N can cause problems with HDBSCAN / DBSCAN, however I have not seen any discussion of what small N might be and was wondering if there were any ball park figures that ...
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17 views

Clustering of very high dimensional data and large number of examples without losing info in dimensions

I'm trying to get a grasp on scalability of clustering algorithms, and have a toy example in mind. Let's say I have around a million or so songs from $50$ genres. Each song has characteristics - some ...
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38 views

Using NbClust on datasets that produce some negative eigenvalues. When to exclude data, when to force to positive, when to exclude test index?

Background on why I am using clustering: I am analyzing data from a multistep biological experiment, where each step is done in batches of varying sizes. I want to account for any biases that might ...
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22 views

How to confirm that the differences between clusters are statistically significant? [closed]

I have a DataFrame of page navigation behavior from visits to an e-commerce website. My independent variable is Revenue, which is simply binary (1 for Revenue ...
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10 views

Which clustering method to use for customer segmentation? [closed]

in my business I often face the problem to group customers / participants into groups based on buying / transaction behavior. Most of the time you have several factors which can be seen as your ...
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1answer
17 views

K-means which normalization fits

Hi am working on a business dataset, where I want to group the participant in k-means based on some features. The problem is I have to create this features upfront, so that I combine different ...
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1answer
11 views

Should we most of the time use Ward's method for hierarchical clustering?

By browsing notebooks on the web, I see that most of the time Ward's method is used for hierarchical clustering. What could explain its popularity? Does it mean that in general it performs better than ...
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1answer
25 views

Mixture model on binary + continuous data

If I have a dataset of continuous variables (that I can assume are normally distributed), I can identify subgroups using a Gaussian mixture model and implement. Likewise if I have binary data I can ...
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16 views

Clustering algorithm for mixed data with non constant categorical variables

I have the following scenario, imagine that I have a dataset as follows: ...
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1answer
26 views

How to compute probability distribution to initialize k-means++ cluster centroids?

I am trying to implement my own k-means algorithm without external libraries/modules (with the exception of numpy). I have recently learned about the k-means++ algorithm; to my understanding, it ...
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3answers
32 views

Cluster categorical data (survey data)

I have a dataset containing around 800 observations: It's a dataset collected via a survey; each row is a dataset filled with information re. diet habits, physical activity, the fact of taking ...
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13 views

Can a k-means cluster use different measures for homogeneity and heterogeneity?

TL;DR: Is there an existing k-means clustering algorithm that can have different weights for the (minimized) in-group distance measure and the (maximized) between-group measure? Or, better yet, can ...
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1answer
8 views

Is there a (positive) correlation between extrinsic and intrinsic cluster evaluation metrics?

Is there any studies/research on the correlation between extrinsic (Entropy, purity, B³ F1, ARI, etc.) and intrinsic (Silhouette, Calinski and Harabasz, Davies-Bouldin, etc.) clustering evaluation ...
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1answer
30 views

Is there a way to generate artificial data from clusters?

Suppose you have a data set that can be clustered as follows: Is there a way to generate data that would fit inside, say, the red bubble, or blue bubble? This can definitely be done in two-dimensions,...
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1answer
13 views

Formal methods for identifying characteristics of a Cluster

I have a data-set of about 100 columns (predictors). To this I have appended a categorical column, with three discrete levels, 1-3. These levels are derived by grouping predictions from a model (...
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1answer
27 views

Affinity Propagation evaluation with sklearn metrics [closed]

I did some clustering with sklearn's Affinity Propagation and now I want to check how my clustering performs. I know there are a lot of metrics to check that, but some questions have appeared: Which ...
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1answer
23 views

Significance tests for differences in performance of many clustering algorithms

I have $n$ clustering algorithms which are trained and evaluated on the same dataset, and I want to test whether the differences in their performances are significant or not. The dataset is PAN17-...
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11 views

Fuzzy clustering on non time-series data and the Mfuzz package

I am trying to apply the fuzzy clustering on a dataset that does not have the time series format. I read some documents about the fuzzy c-means and the package Mfuzz in R. As to my understanding, the ...
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1answer
28 views

What is the difference between Zero Shot Learning and clustering?

I recently found out about ZSL and to me, it is very similar to a clustering algorithm with one difference: a clustering algorithm such as DBSCAN doesn't need to have a pre-defined group of feature ...
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23 views

How to read/interpret a distance matrix?

I ran some data through scikit's MeanShift clustering and had it spit out a distance matrix. I don't know how to interpret the image or understand the value it provides. Just looking for a clear ...
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12 views

Unsupervised Clustering high dimentional data not having estimation for K

I have a dataset (all numerical) of 50K records containing 500 features. we are trying to find fingerprints. Meaning that we would like to cluster the data and report one of the nodes in each cluster ...
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How to do graph clustering on a knowledge base with relations?

Say I have some (hyper)graph of nodes connected by n-ary relations--how could I do community detection to find the K-archetypal subgraphs for downstream graph-isomorphism comparison?
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1answer
78 views

K-means classifies 96% of my data in 1 cluster. Any suggestions to improve the results?

Problem: K-Means clustering shows 96% of my data belongs to one cluster. How can I improve my results or should I conclude that no cluster exists in my dataset. Dbscan clustering shows 1 cluster ...
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25 views

How can I do subject clustering in a high dimension?

I am working on a dataset with 200 participants' data. For each participant, we collected 20-70 days' data. After data engineering, we got features over 300 dimensions. Do we have any way to cluster ...
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37 views

How to search for irregular signals: Fourier, DWT or k-means?

See my notebook here I want to search for irregular time signals in a data set of ~3 500 000 time signals. I can't give a clear definition of irregular signal, but it must fulfil the criteria of: not ...
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1answer
23 views

Am I right that Calinski-Harabasz index (Pseudo-F) can not be calculated from a distance matrix other than euclidean?

Part: I wonder if one could calculate the Calinski-Harabasz index when only having a distance matrix (and a cluster solution, of course). As you need the within and between sum of squares to come up ...
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25 views

Calculating F-measure in clusterings comparison

In “A comparison of Extrinsic Clustering Evaluation Metrics based on Formal Constraints Technical Report” on page 16 there is some simple example with metric results. According to the first column (...
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1answer
19 views

How to interpret the different cluster sizes in Silhouette plot?

I created silhouette plots for my clustering models by following: this link I want to know what does the different cluster sizes mean and how they were generated?? I understand that thicker size ...
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10 views

analytic weights when the outcome is a standard deviation

I have a research question evaluating the longitudinal divergence of a profit index across businesses within a market. The index is continuous. I plan to use a market-level random-effects model where ...
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16 views

Can I use a bayesian spatio-temporal model in cluster areas I chose from local Moran's I?

I have crime rates for municipalities in a state with hourly frequency. I want to make predictions about the spatio-temporal behavior of that variable. Is it possible to run a local Moran's I to ...
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1answer
15 views

How to compare distributions of values by the way they cluster along a line?

This is an optimization problem in Sudoku. I use a very fast brute force recursive fill-and-backtrack algorithm to count the number of solutions. This proceeds from the top-left to the bottom-right ...
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1answer
45 views

Weighting in Likert Scale results

I have referred to similar questions on this topic, but the problem presented then was not quite in line with my research, so I have created a new question. My research is the following: I have ...
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1answer
18 views

SSE not decreasing with increase in number of clusters

So as far as I know, SSE should decrease( or just never increases) as the number of clusters increases. I have an implementation of K-means where the parameter k was supplied as 5,10,15,20,25 and 30 ...
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2answers
31 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 ...
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37 views

Supervised random forest worked example [closed]

I'm following the first 3 steps for unsupervised random forests from here https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0122705&type=printable The steps are: The ...
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10 views

K means clustering on principle components with low explained variance ratios?

Say I have a situation where I do PCA with three components on a data set and the summed explained variance ratios of the three components is relatively low, say less than 0.5. If I were to then do k ...
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2answers
67 views

Clustering groups of data with Machine Learning

I want to cluster objects. There are two attributes (one categorial and one numerical). They should be clustered after the numerical attribut. But observations with the same categorical value should ...
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1answer
14 views

Using k-means to segment customers in the positive class

I have some labeled data (0=didn’t cancel, 1=canceled) that I am creating a model for in my marketing class. On top of predicting who is likely to cancel, I’d like to explore the possibility of ...
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21 views

Mixture of Multinomials

I have implemented a Naive Bayes Model for a mixture of independent Bernoulli. Where the conditional probability can be written as: $\mathbb{P}(Y=j | X) \propto \omega_{j} \prod_{i=1}^{d} \mu_{i, j}^{...
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9 views

Exponential random on clustered graphs

In, short am using time use data and I am aiming to represent the way everyday activities connect in time and space. So i created the above graph in Gephi. The nodes are activities and edges are 2nd ...
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2answers
32 views

Can Gaussian Mixture Model Clustering tell me something about the distribution of my data?

I have 10,000 vectors originating from 5 separate classes (2,000 each). I use Gaussian Mixture Model clustering (in Python) to cluster the 10,000 vectors, telling the algorithm to cluster the data ...
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1answer
24 views

k-means clustering issue voice data

I'm getting an issue in my k-means I don't know if it my data-set or what anything else. Why i got thia flowing point in the right side of the image? ...
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1answer
34 views

Including binary data during pca [closed]

I'm doing some PCA on scaled features but where I also have some binary variables. When I include the binary features they seem to really impact the PCA and I'm concerned that they will also ...
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2answers
45 views

Cluster quality internal validity after PCA

Last week I asked: Compare clusters quality (internal validity) after and before dimensionality reduction by PCA I've been trying to calculate internal validity for clusters after PCA using the iris ...
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1answer
41 views

How to find better solutions for the k-means problem than by using the k-means/k-means++ algorithm?

The $k$-means problem in its common form can be stated as follows: Given a data set $\mathcal{X}=x_1, ..., x_n$ consisting of $d$-dimensional vectors find a set $C = c_1,...,c_k$ of $d$-dimensional ...
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9 views

How may I determine the optimal interval amplitude within a 1D dimension? [closed]

I have a 1D dataset where the unique dimension has a sample of 28.000 salaries. I'm looking to find how many classes should I use and what is the best amplitude interval to plot something like a ...