IMPLEMENTATION ANALYSIS OF IN-PROCESSING ALGORITHMS THAT MEET CRITERIA OF MONOTONIC SELECTIVE RISK ON FAIRNESS AND ACCURACY IN MACHINE LEARNING

The tradeoff between fairness and accuracy is a common issue in machine learning model development, particularly when the data used contains biases. Models that prioritize accuracy often achieve optimal results in terms of predictions but frequently sacrifice fairness. The primary challenge in th...

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Bibliographic Details
Main Author: Pradipta, Nayotama
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/86174
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Institution: Institut Teknologi Bandung
Language: Indonesia
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