Until now, this approach, which allows to explain some classic clustering criteria such as the well-known k -means criteria and to propose general criteria, has been developed to classify a set of objects measured on a set of variab 基群分析在混合物模型成为了一种古典和强有力的方法。 直到...
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...
The algorithm used by BAYPASS is well suited to study systems involving nested or hierarchical population structure (Gautier 2015), which is particularly common in dendritic habitats such as freshwater (Thomaz et al. 2016). We tested for GEA associations accounting for assumed population demographic ...
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...
4C). Hierarchical clustering evaluation of differentially expressed miRNAs indicated that the control and PS NPs samples were clustered together (Fig. 4D). The relevant information is shown in Table S3. A total of 7 miRNAs were not homologous with humans, including miR-667–3p, miR-3084–3p, ...
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...
their chromosomal structures are highly similar44,45. First, we compared theSalix purpurea v5.1genome with thePopulus trichocarpa v3.1genome, and the BLASTN algorithm was applied for analysis with an E value cutoff of 10-10. Then, we used the Entrez ID of homologousPopulus trichocarpagenes for...
Repeating earthquakes, or repeaters, affecting overlapping rupture patches with a similar focal mechanism, have important implications to track fault slip rates, aseismic deformation, slow earthquakes and earthquake nucleation processes. They are often d