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?
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...
That younger individuals perceive the world as moving slower than adults is a familiar phenomenon. Waiting for the next birthday to come seems “forever” for children, but the older we get, the faster “time flies”. Yet, it is an open question why that is. One possible answer relates to...
algorithm for adolescents and adults are presented. The first two columns display the top and back views for the Adults, while the last two columns depict the top and back views for the Adolescents. IT inferior temporal cortex, FT fronto-temporal cortex, TO temporo-occipital cortex, MF medial...
the population structure could be divided into more sub-clusters28,44, varying in number on the basis of dataset and clustering algorithm. Considering that the aim of this work was to study the major evolutionary forces shapingS. marcescenspopulation structure, we decided to focus on the five ma...
Answer to: Explain the differences between public, private, and community clouds. What are some of the factors to consider when choosing which...
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...
However, many works in the literature use the network average clustering coefficient to analyze network properties. The network average clustering coefficient weights more nodes with a low degree (as discussed in the Supplementary Information Sect. 2). Thus, it is not a correct measure to analyze ...
assumption is that words used in similar ways, at such a very large scale, have similar meanings. Here, we project movies into a semantic space using their movie description: the closer movie summaries are semantically, the closer movies will be into this space. Then, we use the K-Means ...