Ethical concerns related to bias and fairness

Sep 27, 2018 ... In this paper, we study counterfactual fairness in text classification, which asks the question: How would the prediction change if the sensitive attribute ... May 13, 2021 ... I have a few text classifiers that i am testing out, and they work well for data that does fit into any predefined category. In text classification, we are given a description $\onedoc \in \mathbb{X}$ of a document, where $\mathbb{X}$ is the document space ; and a fixed set of ... This page describes how to prepare text data for use in a Vertex AI dataset to train single-label and multi-label classification models. ... classification result. T This method is a classification enhancement method that can classify patent text alone or enhance the accuracy of various types of ... Apr 4, 2019 ... In this study, we propose a new approach which combines rule-based features and knowledge-guided deep learning models for effective disease classification. ... Text Line Database · Cover of Improving Text Classification with Boolean Retrieval for Rare Categories: A Case Study Identifying. Improving Text Classification ... Author(s): ROSARIO, RYAN ROBERT | Advisor(s): Wu, Yingnian | Abstract: Text classification typically performs best with large training sets, but short texts ... SST-2 Binary text classification with XLM-RoBERTa model. Author: Parmeet Bhatia. Overview. This tutorial demonstrates how to train a text classifier on ... Jun 27, 2022 ... What is Text Classification? Text Classification is the process of categorizing text into one or more different classes to organize, structure, ...