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clustering

DPCfam Workstation version. Runs on Linux-based systems. Developed and tested on Ubuntu 18. DPCfamW uses the moodycamel::ConcurrentQueue library ( https://github.com/cameron314/concurrentqueue ) freely available provided citation (Simplified BSD license). This version replicates the pipeline used in to anlayze UniRef50 (v. 2017_07) as in Unsupervised protein family classification by Density Peak clustering, Russo ET, 2020, PhD Thesis ( http://hdl.handle.net/20.500.11767/116345 ), but with smaller datasets. Largest dataset we analysed is the TESTproteins_cd50.fasta datased we provide in this package. Due to memory bounds we do not guarantee that the abalysis of largest datasets is acheivable with this version.

Implementation of Altieri, F., Pietracaprina, A., Pucci, G., & Vandin, F. (2021). Scalable distributed approximation of internal measures for clustering evaluation. In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) (pp. 648-656). Society for Industrial and Applied Mathematics.

Capstone 1: Caterpillar Tube Pricing Prediction & Categorization. Capstone 2:Pipeline Multi-Leak Classification.

Machine Learning - Regression Problem

This repository contiains the implementation of DPC-based algorithm as described in Russo, E.T., Laio, A. & Punta, M. Density Peak clustering of protein sequences associated to a Pfam clan reveals clear similarities and interesting differences with respect to manual family annotation. BMC Bioinformatics 22, 121 (2021). https://doi.org/10.1186/s12859-021-04013-x. Note that the implementation has been written with the puropose of analysing, on a traditional workstation (8GB ram, 4-8 cores), query datasets with up to 5000 proteins, as those analysed in the reference paper.

EECluster is software tool for managing the energy-efficient allocation of the cluster resources. EECluster uses a Hybrid Genetic Fuzzy System as the decision-making mechanism. See pirweb.edv.uniovi.es/eecluster.

Python libraries for Principal Component Analysis-based (PCA) model order reduction, clustering and data analysis.

pyAMNESIA: a python pipeline for analysing the Activity and Morphology of NEurons using Skeletonization and other Image Analysis techniques.

The source code for TensorClustering as described in the IEEE TPAMI 2019 paper: Large-scale Urban Reconstruction with Tensor Clustering and Global Boundary Refinement.

The source code for TensorClustering as described in the IEEE TPAMI 2019 paper: Large-scale Urban Reconstruction with Tensor Clustering and Global Boundary Refinement.

Projet d'analyse de 3 jeux de données en clustering. Les résultats serviront à la rédaction d'un article sur le blog d'Octo.

Clustering documents to get an overview of a corpus

Машинное обучение. Анализ алгоритмов кластеризации

Trabajo Final de Grado de Ingeniería en Informática de la Facultad Politécnica de la Universidad Nacional de Asunción.

Testing functions and features of a music production utility app.

Clustered hosting

Code for Bayesian Deep Learning Workshop, NIPS 2017

Is Simple Better?: Revisiting Simple Generative Models for Unsupervised Clustering

Simuler l'impact électoral d'un changement de taille des circonscriptions législatives.

This repo presents performance comparisons between a serial implementation, a MPI based and a Spark based implementation of a document clustering algorithm

Implementation of the Clustering K-Nearest Data Mining Algorithm base on Java