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Individualized Group Learning

Many massive data sets are assembled through collections of information of a large number of individuals in a population. The analysis of such data, especially in the aspect of individualized inferences and solutions, has the potential to create significant value for practical applications. Traditio...

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Bibliographic Details
Published inJournal of the American Statistical Association Vol. 118; no. 541; pp. 622 - 638
Main Authors Cai, Chencheng, Chen, Rong, Xie, Min-ge
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis 02.01.2023
Taylor & Francis Ltd
Subjects
Americans
Bayesian inference
bias
Big Data
Clustering
Cognitive style
data analysis
data collection
Datasets
Empirical analysis
Fusion learning
Group learning
Heterogeneity
Individualized Inference
Kernel smoothing
Learning
Massive data points
Nonparametric
Nonparametric statistics
Regression analysis
Similarity meaures
Statistical inference
Statistical methods
Statistics
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  • ikona citování Cite this
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    • Export to RIS
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