Belangrijkste concepten
No-rejection learning strategy in regression with rejection ensures consistency and performance improvement.
Statistieken
"The model NN+kNNRej has a uniform advantage over the other algorithms across different datasets."
"SelNet with α = 0.5 generally performs better than SelNet with α = 1 in the fixed-budget setting."
Citaten
"No-rejection learning strategy ensures consistency and performance improvement in regression with rejection."
"The rejector can be viewed as a binary classifier assigning prediction tasks to predictor or human."
"Truncated loss serves as a proxy for the original loss, with the squared loss as a surrogate."