Oct 26, 2012 · Abstract. This paper proposes a simple strategy for combining binary classifiers with imprecise probabilities as outputs.

This paper proposes a simple strategy for combining binary classifiers with imprecise probabilities as outputs. Our combination strategy consists in ...

This paper proposes a simple strategy for combining binary classifiers with imprecise probabilities as outputs. Our combination strategy consists in ...

Abstract. This paper proposes a simple strategy for combining binary classifiers with imprecise probabilities as outputs. Our combination strat-.

The local discounting strategy proves to give very good results compared both to single classifier approaches and to classifier combination schemes using a ...

In this paper, we handle missing values in both training and test sets with uncertainty and imprecision reasoning by proposing a new belief combination of ...

Correcting Binary Imprecise Classifiers: Local vs Global Approach by Sébastien Destercke, Benjamin Quost published in Lecture Notes in Computer.

Combining Binary Classifiers with Imprecise Probabilities · hmtl icon ... Correcting Binary Imprecise Classifiers: Local vs Global Approach · hmtl icon.

This paper proposes a simple strategy for combining binary classifiers with imprecise probabilities as outputs. Our combination strategy consists in ...

Jan 15, 2024 · The quantum discriminator takes as input the binary features extracted from a given datum along with a prediction qubit, and outputs the ...