Filter can be a clustering filter, segment filter, or bitmap filter. For more information, see Column-oriented storage. Example 1: A query hits indexes. BEGIN; CREATE TABLE column_test ( "id" bigint not null , "name" text not null , "age" bigint not null ); CALL set_table_...
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...
For arguing between agents, we used the Jason multi-agent platform. We assume different knowledge base and reasoning capabilities for each agent. The agents have their own optical coherence tomography (OCT) images on which they apply a distinct machine learning algorithm. The learned model is used...
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...
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...
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 ...
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...
We found that the majority of host species showed significant clustering for MNTD, with close to half for MPD (Fig.6). Very few species showed phylogenetic evenness. Of those that did, all belonged to the Artiodactyla, except for the long-eared owl (Asio otus; Fig.6). In support of the...
Clustering analysis on empirical and simulated neuronal responses To evaluate the optimal number of clusters that can best describe both the empirical weight distributions as well as the simulated neuronal responses, Dirichlet process with Gaussian mixture modelling58and time-series K-Means analysis81were...