We build risk classes according to each region’s risk of exposure to COVID-19 cases by performing a 1-dimensional k-means38 unsupervised clustering algorithm on the number of cases for each wave, with a varying number of clusters: we found that two clusters is an optimal choice, in terms...
Discuss the pros and cons of k-means clustering compared to hierarchical clustering. What is the difference between classification and regression? What is a classification algorithm? What is unsupervised classification? What is rule-based classification?
The global genomic datasetstrains weregrouped via Principal Coordinates Analysis (PCoA) and unsupervised clustering algorithm K-means, using independently tree patristic distances, CoreSNP distances, Mash distances and Jaccard distances computed on the gene presence absence. The Average Nucleotide Identity (...
TreeSHAP is an algorithm to compute SHAP values for tree ensemble models such as decision trees, random forests, and gradient boosted trees in a polynomial-time proposed by Lundberg et. al (2018)¹. The algorithm allows us to reduce the complexity from O(TL2^M)to O(TLD^2) (T = numb...
The agents have their own optical coherence tomography (OCT) images on which they apply a distinct machine learning algorithm. The learned model is used to extract diagnosis rules. With distinct learned rules, the agents engage in an argumentative process. The resolution of the debate outputs a ...
The Dynamic Imaging of Coherent Sources (DICS) beamforming and applying the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm on the results of the DICS beamforming, in order to localize the generators of the activity of the three frequency bands of interest (TBA, AB...
Discuss the pros and cons of k-means clustering compared to hierarchical clustering. What was the original cloud storage? What is the difference between privacy and data security? What is enterprise cloud storage? What is another name for clo...
The Dynamic Imaging of Coherent Sources (DICS) beamforming and applying the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm on the results of the DICS beamforming, in order to localize the generators of the activity of the three frequency bands of interest (TBA, AB...
The SOM is a competitive learning algorithm that tries to find a low-dimensional representation of the data in such a way that the topological ordering properties of the original data are preserved. These two models are analyzed in Supplementary Information Sect. 5, where both models are compared...
three-component waveforms (up to 4 Hz) for two co-located random double-couple mechanisms based on a regional velocity model for Mayotte27. The synthetics are calculated using the pyrocko toolbox and a precalculated Green’s function database91obtained via the orthonormal propagator algorithm QSE...