Decision making based on Item Response Theory b parameter in ensemble rankings
DOI:
https://doi.org/10.51359/2317-0115.2022.256869Keywords:
decision-making, item response theory, ensemble, classificationAbstract
Decision-making based on the aid of computerized systems is a complex task and the target of many adjustments to avoid classification errors. Evaluating the classifications by the hits of the algorithms and associating these hits with the Difficulty parameter (b) of the IRT in agreement with the Kappa statistics provides greater security to the user of computerized systems. In this evaluation between the undersample and oversample groups, it was possible to select specific groups of cluster algorithms basedon the 5% confidence interval and agreement intensity greater than 0.9968, identifying Perfect agreement (0.48%) in the SMOTE groups.
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