Summer read: a new paper on model-based clustering just appeared in Computo!

Julien Jacques and Brendan Thomas Murphy publish a new method for clustering multivariate count data. The method combines feature selection and clustering, and is based on conditionally independent Poisson mixture models and Poisson generalized linear models.

On simulations, the Adjusted Rand Index (ARI) of the model with selected variables is close to the optimal ARI obtained with the true clustering variables.

The paper and accompanying R code are available at https://computo-journal.org/published-202507-jacques-count-data/

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

Clustering Machine Learning Certification

Take the exam online: https://www.edchart.com/certificate/clustering-machine-learning-certification-exam-free-test
Get your verified digital credential: https://www.credly.com/org/edchart-technologies/badge/edchart-certified-clustering-machine-learning-subje

EdChart now offers the Clustering Machine Learning Certification, recognized globally and trusted by professionals. Take the online exam from anywhere in the world, and pay only if you pass.

Ein lang ersehnter Wunsch von mir: Eigene #Clustering Methoden in #OpenRefine benutzen.

Verfügbar seit Version 3.9.0 und funktioniert seit 3.9.3 auch mit #Jython und #Clojure.

Hier eine Anleitung zur Benutzung im #FDMLab Blog.

https://fdmlab.landesarchiv-bw.de/workshop/openrefine-fortgeschrittene/19-erweitertes-clustering/

Clustering Workbench of the Carrot2 search engine is working now. It can
cluster search results by 3 algorithms:
Lingo, STC, or k=means. STC is Suffix Tree Clustering method, a fast, phrase-based clustering method that groups documents based on common, frequent phrases. The screenshot shows search results using Lingo clustering for query:
"survey of AI tools for systematic reviews."

https://search.carrot2.org/#/workbench

#research #academia #Carrot2
#systematicReview
#clustering #Lingo #STC #k-means

'Curvature-based Clustering on Graphs', by Yu Tian, Zachary Lubberts, Melanie Weber.

http://jmlr.org/papers/v26/24-0781.html

#clustering #communities #clusters

Exciting news, our paper is out!

"Behavioral Clusters and Lesion Distributions in Ischemic Stroke, Based on NIHSS Similarity Network" on Springer Journal of Healthcare Informatics Research https://rdcu.be/efgma

With my co-first-author Andrea Zanola and co-authors, we explore the relations between behavioral measures of impairment after stroke, and the underlying brain lesions.
Rather than focusing on covariances at the population level, we first cluster individual behavioral phenotypes, and then explore the typical and significant lesions of each cluster.

Our technique, Repeated Spectral Clustering is performed on a similarity network (derived from the General Distance Measure, handy for ordinal scales!), and the partitions are statistically robust thanks to the aggregation of results from multiple random initializations.

We end up with 5 clusters, 3 of which show reknown principal components of deficits (Left Motor, Righ Motor, Language), and their associate lesions.

Interestingly, this multi-item and multimodal approach allows to distinguish different etiologies for the same deficits, thanks to their different behavioral associations, and the different lesions characterizing each cluster. Even when the single NIHSS measure is a bit "vague"...

We hope that popularizing the General Distance Measure, Repeated Spectral Clustering and this clustering perspective aside of PCA / CCA studies can inspire multimodal approaches in other neuroscientific and biomedical domains!

Many thanks to our co-authors, Antonio Luigi Bisogno, Silvia Facchini, Lorenzo Pini, Manfredo Atzori and Maurizio Corbetta for data, analytic and medical insights, and their guidance throughout the whole process!

The clustering behavior of sliding windows

https://arxiv.org/abs/2503.14393

'Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions', by Dapeng Yao, Fangzheng Xie, Yanxun Xu.

http://jmlr.org/papers/v26/23-0142.html

#sparse #clustering #clusters

A Methodology For The Multitemporal Analysis Of Land Cover Changes And Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery - A Case Study Of The Aburrá Valley In Colombia
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https://doi.org/10.3390/rs17030554 <-- shared paper
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#GIS #spatial #mapping #SyntheticApertureRadar #SAR #remotesensing #multitemporalanalysis #landcover #landcoverchange #clustering #kurtosis #fuzzylogic #kernelbasedmethod #machinelearning #spatialanalysis #spatiotemporal #geostatistics #model #modeling #AburráValley #Columbia #urban #urbanexpansion #population #growth #topography #monitoring #satellite #sentinel #valley #landuse #distribution #infrastructure #building #roads #naturalresources #environmental #conservation #monitoring #multitemporal

I’m doing a drive swap on my Mini Cluster, swapping out HDDs for SSDs.

#CosplayAsSysadmin
#Clustering

**OptimOTU: Taxonomically aware OTU clustering with optimized thresholds and a bioinformatics workflow for metabarcoding data**

https://arxiv.org/abs/2502.10350