DNN2LR

2000년 도입 · 논문 2편에서 사용

DNN2LR is an automatic feature crossing method to find feature interactions in a deep neural network, and use them as cross features in logistic regression. In general, DNN2LR consists of two steps: (1) generating a compact and accurate candidate set of cross feature fields; (2) searching in the candidate set for the final cross feature fields.

출처: DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data

소개 논문: DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data