AutoGluon, FastAI, Py-Custom, TabNet kNN, LDA, Naïve Bayes, Logistic Regression, SVM Bagging: Random Forest Boosting: ADABoost, Gradient Boosting, XGBoost Unsupervised UNS META-UNS COF, FastABOD, G-Means,K-Means, LOF, ODIN, One-Class SVM, HBOS, LDCOF, SDO, SOM, iForest Bagging: ensem...
Using a three-day lag, we estimated the effects of PM10 and O3 on mortality through a hybrid approach involving distributed lag non-linear models and conditional logistic regression. Adjustments to the models incorporated the average daily temperature and average daily absolute humidity values. Using ...
Graph Neural Networks for Anomaly Detection in Industrial Internet of Things. IEEE Internet Things J. 2022, 9, 9214–9231. [Google Scholar] [CrossRef] Mkrtchyan, G.V.; Abdelmohsen, K.; Andreux, P.; Bagdonaite, I.; Barzilai, N.; Brunak, S.; Cabreiro, F.; Cabo, R.D.; Campisi,...
(UMAP), and cells were clustered together using a graph-based clustering approach. Cells were first embedded in a K-Nearest Neighbour (KNN) graph and then iteratively grouped together with the number of modules optimised using the Louvain algorithm. We found that the resultant datasets are very ...
In this case, the use of the k-core algorithm in Pajek enables us to visualize, for example, a cluster of title words focusing on exponential random graph models [33]. This cluster is more related to the word "social" than to "network" given this algorithm. Note that the possibility ...