Searched for: subject%3A%22Selection%255C+bias%22
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document
van Hoorn, Timo (author)
Sample selection bias occurs when the selected samples in a subset of the original data set follow a different distribution than the samples from the original data set. This type of bias in the training set could result in a classifier being unable to predict samples from a testing data set optimally. Domain adaptation techniques try to adapt...
bachelor thesis 2023
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TOCIU, Andrei (author)
Importance weighting is a class of domain adaptation techniques for machine learning, which aims to correct the discrepancy in distribution between the train and test datasets, often caused by sample selection bias. In doing so, it frequently uses unlabeled data from the test set. However, this approach has certain drawbacks: it requires...
bachelor thesis 2023
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Khan, Zeeshan (author)
Sample selection bias is a well-known problem in machine learning, where the source and target data distributions differ, leading to biased predictions and difficulties in generalization. This bias presents significant challenges for modern machine learning algorithms. To tackle this problem, researchers have focused on developing domain...
bachelor thesis 2023
document
Tepeli, Y.I. (author), Seale, C.F. (author), P. Gonçalves, Joana (author)
Motivation<br/><br/>Anti-cancer therapies based on synthetic lethality (SL) exploit tumour vulnerabilities for treatment with reduced side effects, by targeting a gene that is jointly essential with another whose function is lost. Computational prediction is key to expedite SL screening, yet existing methods are vulnerable to prevalent selection...
journal article 2023
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Seale, C.F. (author), Tepeli, Y.I. (author), P. Gonçalves, Joana (author)
Motivation<br/>Synthetic lethality (SL) between two genes occurs when simultaneous loss of function leads to cell death. This holds great promise for developing anti-cancer therapeutics that target synthetic lethal pairs of endogenously disrupted genes. Identifying novel SL relationships through exhaustive experimental screens is challenging,...
journal article 2022
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Troost, A.A. (author), van Ham, M. (author), Janssen, H.J. (author)
The non-random selection of people into neighbourhoods complicates the estimation of causal neighbourhood effects on individual outcomes. Measured neighbourhood effects could be the result of characteristics of the neighbourhood context, but they could also result from people selecting into neighbourhoods based on their preferences, income,...
journal article 2021
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van Wee, G.P. (author), Cao, Jason (author)
This chapter gives an overview of the current debates on residential self-selection and presents a related research agenda. Here, we define residential self-selection as “the tendency of people to choose residential locations based on their travel abilities, needs and preferences.” Debates relate to theory/causalities (including the role of...
book chapter 2020
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van Ham, M. (author), Boschman, S.E. (author), Vogel, M.S. (author)
Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select...
journal article 2018
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van Ham, M. (author), Boschman, S.E. (author), Vogel, M.S. (author)
Studies of neighbourhood effects often attempt to identify causal effects of neighbourhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research and it has been repeatedly argued that estimates of neighbourhood effects are biased as people non-randomly...
working paper 2017
document
Boschman, S.E. (author)
Despite a large body of research on neighbourhood effects, there are no clear conclusions how much, if any, independent effect the neighbourhood has on its residents. This is largely due to selection effects. It is therefore crucial to gain more insight in selective residential mobility and neighbourhood choice. A better understanding of...
doctoral thesis 2015
Searched for: subject%3A%22Selection%255C+bias%22
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