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Found 4 papers, 2 papers with code
Explanation-by-Example Based on Item Response Theory
Intelligent systems that use Machine Learning classification algorithms are increasingly common in everyday society.
Data vs classifiers, who wins?
The experiments covered by Machine Learning (ML) must consider two important aspects to assess the performance of a model: datasets and algorithms.
NASirt: AutoML based learning with instance-level complexity information
Designing adequate and precise neural architectures is a challenging task, often done by highly specialized personnel.
Decoding machine learning benchmarks
This work applied IRT to explore the well-known OpenML-CC18 benchmark to identify how suitable it is on the evaluation of classifiers.
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