# Classification from Ambiguity Comparisons

@article{Cui2020ClassificationFA, title={Classification from Ambiguity Comparisons}, author={Zhenghang Cui and Issei Sato}, journal={ArXiv}, year={2020}, volume={abs/2008.00645} }

Labeling data is an unavoidable pre-processing procedure for most machine learning tasks. However, it takes a considerable amount of time, money, and labor to collect accurate \textit{explicit class labels} for a large dataset. A positivity comparison oracle has been adapted to relieve this burden, where two data points are received as input and the oracle answers which one is more likely to be positive. However, when information about the classification threshold is lacking, this oracle alone…

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