Abstract
This paper discusses transductive versions of conformal predictors and inductive conformal predictors. The transductive versions are computationally inefficient for long test sequences, but it turns out that apparently crude "Bonferroni predictors" are about as good in their informational efficiency and vastly superior in computational efficiency. The paper explores transductive predictors both theoretically and experimentally, in the latter case using the standard USPS data set of handwritten digits.
Original language | English |
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Article number | 1560001 |
Journal | International Journal on Artificial Intelligence Tools |
Volume | 24 |
Issue number | 6 |
DOIs | |
Publication status | Published - 21 Dec 2015 |
Keywords
- Conformal predictors; inductive conformal predictors; transduction; Bonferroni adjustment.