Estimating from No Data: Deriving a Continuous Score from Categories
中文摘要
本文介绍了如何利用低容量网络，在仅有类别标签的情况下，通过数学方法推导出细粒度的连续评分。
English Summary
This article explains how to use low-capacity networks to derive fine-grained continuous scores when only categorical labels are available for training.
Original Excerpt
A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training The post Estimating from No Data: Deriving a Continuous Score from Categories appeared first on Towards Data Science.