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 (...
We can also aggregate SHAP values for many predictions to calculate different metrics, such as feature importance defined as the mean of absolute values of SHAP values. If you are interested in learning more about SHAP values, we recommend reading a chapter devoted to them in one of these book...
(Beamforming Analyses section). Connectivity arrows show the information flow from one cluster to another one, while the arrow thickness and the size of the arrowhead is proportional to the connectivity strength. For the linear connectivity patterns, the mean absolute values of all non-self linear...
(Beamforming Analyses section). Connectivity arrows show the information flow from one cluster to another one, while the arrow thickness and the size of the arrowhead is proportional to the connectivity strength. For the linear connectivity patterns, the mean absolute values of all non-self linear...
We can also just take the mean absolute value of the SHAP values for each feature to get a standard bar plot (produces stacked bars for multi-class outputs): shap.plots.bar(shap_values) SHAP has specific support for natural language models like those in the Hugging Face transformers library...
We can also just take the mean absolute value of the SHAP values for each feature to get a standard bar plot (produces stacked bars for multi-class outputs): shap.plots.bar(shap_values) Natural language example (transformers) SHAP has specific support for natural language models like those in...
Clustering was carried out over the backbone and Cβ atoms of each construct using the Daura algorithm (66). The degree of the open/closed N-cTnC conformational change and protein stability were assessed through measurements of the solvent-accessible surface area, the interhelical angles, and the...
Model fitting to experimental data was done by nonlinear curve-fitting in the least-squares sense using the Levenberg-Marquardt algorithm (MATLAB built-in function). Briefly, the best-fitting parameter set was derived by fitting model to mean value of bond lifetime vs force profile, and SE of...