data requirements

labelled data

Requires datasets with ground truth labels

25 techniques
GoalsModelsData TypesDescription
Integrated Gradients
Algorithmic
Architecture/neural Networks
Paradigm/parametric
+3
Any
Integrated Gradients is an attribution technique that explains a model's prediction by quantifying the contribution of...
Area Under Precision-Recall Curve
Algorithmic
Architecture/model Agnostic
Paradigm/supervised
+2
Any
Area Under Precision-Recall Curve (AUPRC) measures model performance by plotting precision (the proportion of positive...
Monotonicity Constraints
Algorithmic
Architecture/probabilistic/gaussian Processes
Architecture/tree Based
+2
Tabular
Monotonicity constraints enforce consistent directional relationships between input features and model predictions,...
Generalized Additive Models
Algorithmic
Architecture/linear Models/gam
Paradigm/parametric
+2
Tabular
An intrinsically interpretable modelling technique that extends linear models by allowing flexible, nonlinear...
Fairness GAN
Algorithmic
Architecture/neural Networks/generative/gan
Paradigm/generative
+4
Any
A data generation technique that employs Generative Adversarial Networks (GANs) to create fair synthetic datasets by...
Relabelling
Procedural
Architecture/model Agnostic
Paradigm/supervised
+2
Any
A preprocessing fairness technique that modifies class labels in training data to achieve equal positive outcome rates...
Preferential Sampling
Procedural
Architecture/model Agnostic
Paradigm/supervised
+2
Any
A preprocessing fairness technique developed by Kamiran and Calders that addresses dataset imbalances by re-sampling...
Fair Adversarial Networks
Algorithmic
Architecture/neural Networks
Paradigm/discriminative
+6
Any
An in-processing fairness technique that employs adversarial training with dual neural networks to learn fair...
Prejudice Remover Regulariser
Algorithmic
Architecture/linear Models/logistic
Architecture/probabilistic
+5
Tabular
An in-processing fairness technique that adds a fairness penalty to machine learning models to reduce bias against...
Meta Fair Classifier
Algorithmic
Architecture/model Agnostic
Paradigm/supervised
+2
Any
An in-processing fairness technique that employs meta-learning to modify any existing classifier for optimising fairness...
Exponentiated Gradient Reduction
Algorithmic
Architecture/model Agnostic
Paradigm/discriminative
+5
Any
An in-processing fairness technique based on Agarwal et al.'s reductions approach that transforms fair classification...
Multi-Accuracy Boosting
Algorithmic
Architecture/ensemble
Paradigm/discriminative
+3
Any
An in-processing fairness technique that employs boosting algorithms to improve accuracy uniformly across demographic...
Equalised Odds Post-Processing
Algorithmic
Architecture/model Agnostic
Paradigm/discriminative
+3
Any
A post-processing fairness technique based on Hardt et al.'s seminal work that adjusts classification thresholds after...
Reject Option Classification
Algorithmic
Architecture/model Agnostic
Paradigm/supervised
+2
Any
A post-processing fairness technique that modifies predictions in regions of high uncertainty to favour disadvantaged...
Calibration with Equality of Opportunity
Algorithmic
Architecture/model Agnostic
Paradigm/supervised
+2
Any
A post-processing fairness technique that adjusts model predictions to achieve equal true positive rates across...
Equal Opportunity Difference
Metric
Architecture/model Agnostic
Paradigm/supervised
+1
Any
A fairness metric that quantifies discrimination by measuring the difference in true positive rates (recall) between...
Adversarial Training Evaluation
Testing
Architecture/model Agnostic
Architecture/neural Networks
+1
Any
Adversarial training evaluation assesses whether models trained with adversarial examples have genuinely improved...
Chain-of-Thought Faithfulness Evaluation
Testing
Architecture/neural Networks/transformer/llm
Paradigm/generative
+1
Text
Chain-of-thought faithfulness evaluation assesses the quality and faithfulness of step-by-step reasoning produced by...
Constitutional AI Evaluation
Testing
Architecture/neural Networks/transformer/llm
Requirements/white Box
+1
Text
Constitutional AI evaluation assesses models trained to follow explicit behavioural principles or 'constitutions' that...
Few-Shot Fairness Evaluation
Testing
Architecture/neural Networks/transformer/llm
Paradigm/generative
+1
Text
Few-shot fairness evaluation assesses whether in-context learning with few-shot examples introduces or amplifies biases...
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