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Found 3 papers, 2 papers with code
Quantification using Permutation-Invariant Networks based on Histograms
Quantification, also known as class prevalence estimation, is the supervised learning task in which a model is trained to predict the prevalence of each class in a given bag of examples.
Kernel Density Estimation for Multiclass Quantification
Several disciplines, like the social sciences, epidemiology, sentiment analysis, or market research, are interested in knowing the distribution of the classes in a population rather than the individual labels of the members thereof.
Binary Quantification and Dataset Shift: An Experimental Investigation
One finding that results from this investigation is that many existing quantification methods that had been found robust to prior probability shift are not necessarily robust to other types of dataset shift.
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