Parents in north London have been told their children could be excluded from school if they are not fully vaccinated against measles amid an outbreak of the highly-contagious disease. Unvaccinated pupils identified as close contacts of people with measles could be excluded for 21 days in accordance with national guidelines, Enfield Council said in a letter to all parents in the borough in late January. At least 34 children have contracted measles in Enfield so far this year, the UK Health Security Agency (UKHSA) has said, and a number sent to hospital. A local health chief meanwhile told the BBC: We are worried because actually, this is a significantly increased number than what we're used to. Asking unvaccinated, close contacts of measles cases to stay off school is fairly standard practice when there are local outbreaks.

Existing solutions either work under very specific assumptions or achieve bounds that are vacuous in some regimes.

Categorical encoders transform categorical features into numerical representations that are indispensable for a wide range of machine learning models. Existing encoder benchmark studies lack generalizability because of their limited choice of 1. encoders, 2. experimental factors, and 3. datasets. Additionally, inconsistencies arise from the adoption of varying aggregation strategies. This paper is the most comprehensive benchmark of categorical encoders to date, including an extensive evaluation of 32 configurations of encoders from diverse families, with 48 combinations of experimental factors, and on 50 datasets. The study shows the profound influence of dataset selection, experimental factors, and aggregation strategies on the benchmark's conclusions -- aspects disregarded in previous encoder benchmarks.

Deep learning models have been widely used to assist doctors with clinical decision-making.