Results 21 to 30 of about 1,035,049 (261)
iMeta, 2022 The identification of microbial markers adequate to delineate the disease‐related microbiome alterations from the complex human gut microbiota is of great interest.
Shun Guo +4 more
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Synthetic Data Generation for Data Envelopment Analysis
Data, 2023 The paper is devoted to the problem of generating artificial datasets for data envelopment analysis (DEA), which can be used for testing DEA models and methods.
Andrey V. Lychev
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Complexity, 2020 Due to huge amount of greenhouse gases emission (such as CO2), freight has been adversely affecting the global environment in facilitating the global economy.
Zixuan Yu +4 more
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An Adversary Model of Fraudsters’ Behavior to Improve Oversampling in Credit Card Fraud Detection
IEEE Access, 2023 Imbalanced learning jeopardizes the accuracy of traditional classification models, particularly for what concerns the minority class, which is often the class of interest.
Daniele Lunghi +3 more
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Synthetic Data for Feature Selection
, 2023 Feature selection is an important and active field of research in machine learning and data science. Our goal in this paper is to propose a collection of synthetic datasets that can be used as a common reference point for feature selection algorithms.
Firuz Kamalov +2 more
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Predicting the frequencies of drug side effects
Nature Communications, 2020 Currently, the frequencies of drug side effects are determined in randomised controlled clinical trials. Here the authors develop an interpretable machine learning approach to predict the frequencies of unknown side effects for drugs with a small number ...
Diego Galeano +3 more
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Likelihood-Based Finite Sample Inference for Synthetic Data from Pareto Model
Revstat Statistical Journal, 2023 Statistical agencies often publish microdata or synthetic data to protect confidentiality of survey respondents. This is more prevalent in case of income data.
Nutan Mishra , Sandip Barui
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Unsupervised Cyclic Siamese Networks Automating Cell Imagery Analysis
Algorithms, 2023 Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data ...
Dominik Stallmann, Barbara Hammer
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CoRR, 2019 Discussion paper at FATES on the Web ...
Luke Rodriguez, Bill Howe
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The Journal of Privacy and Confidentiality, 2020 Enhancing microdata access is one of the strategic priorities for the Australian Bureau of Statistics (ABS) in its transformation program. However, balancing the trade-off between enhancing data access and protecting confidentiality is a delicate act ...
Chien-Hung Chien +2 more
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