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...
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...
Give a big-O estimate of the complexity of the Base algorithm procedure Base (n: positive integer, b: positive integer greater than 1) q:=n k:=0 while q \ne 0 begin a_k:=q mod b q:= q div b k:= k + 1 Give an example where Dijkstra's algorithm gives the wron...
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...
This comic is a satire of computer programmers, who sometimes forget that not everything can be solved with an algorithm, or of the tendency to think computers are the answer to everything. In the first panel, Megan talks about how the field that she and Hairy work in has a difficult ...
First, finding the version space is not sufficient for classifying examples out of the training set. This is due to possible conflicts between hypotheses. Second, it has been shown that the complexity of the algorithm that identifies VS and VG is very high. In order to palliate that limit, ...
The models were fitted using the numeric BOBYQA-optimiser algorithm implemented in the R-package lme442. The specified models were then compared with likelihood ratio tests. We used the parameters obtained from the winning model to predict responses on the test set to validate the performance of ...
(2) this emerging cluster is related to environmental curiosity through exploration-related content. We use independently two machine-learning algorithms. The random-forest algorithm, based on manually annotated movies, and trained on plot keywords, is designed to detect imaginary worlds in a sample ...
"Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models" (B. Lengerich, S. Tan, C. Chang, G. Hooker, R. Caruana 2019) @article{lengerich2019purifying, title={Purifying Interaction Effects with the Functional ANOVA: An Efficient ...
@article{lengerich2019purifying, title={Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models}, author={Lengerich, Benjamin and Tan, Sarah and Chang, Chun-Hao and Hooker, Giles and Caruana, Rich}, journal={arXiv preprint arXiv:191...