fairness approach

group

Focuses on statistical parity between groups

46 techniques

		Models	Data Types	Description
SHapley Additive exPlanations	Algorithmic	Architecture/model Agnostic Requirements/black Box	Any	SHAP explains model predictions by quantifying how much each input feature contributes to the outcome. It assigns an...
Sobol Indices	Algorithmic	Architecture/model Agnostic Requirements/black Box	Any	Sobol Indices quantify how much each input feature contributes to the total variance in a model's predictions through...
Gradient Saliency	Algorithmic	Architecture/neural Networks Requirements/differentiable +1	Image	Gradient saliency (also known as vanilla gradient saliency) produces visual explanations for image classification models...
Gradient-weighted Class Activation Mapping	Algorithmic	Architecture/neural Networks/convolutional Requirements/architecture Specific +2	Image	Grad-CAM creates visual heatmaps showing which regions of an image a convolutional neural network focuses on when making...
Prototype and Criticism Models	Algorithmic	Architecture/model Agnostic Paradigm/supervised +3	Any	Prototype and Criticism Models provide data understanding by identifying two complementary sets of examples: prototypes...
Influence Functions	Algorithmic	Architecture/linear Models Architecture/neural Networks +6	Any	Influence functions quantify how much each training example influenced a model's predictions by computing the change in...
Demographic Parity Assessment	Algorithmic	Architecture/model Agnostic Paradigm/supervised +1	Any	Demographic Parity Assessment evaluates whether a model produces equal positive prediction rates across different...
Adversarial Debiasing	Algorithmic	Architecture/neural Networks Paradigm/discriminative +4	Any	Adversarial debiasing reduces bias by training models using a competitive adversarial setup, similar to Generative...
Sensitivity Analysis for Fairness	Algorithmic	Architecture/model Agnostic Paradigm/supervised +2	Any	Sensitivity Analysis for Fairness systematically evaluates how model predictions change when sensitive attributes or...
Federated Learning	Algorithmic	Architecture/linear Models Architecture/neural Networks +4	Any	Federated learning enables collaborative model training across multiple distributed parties (devices, organisations, or...
Differential Privacy	Algorithmic	Architecture/model Agnostic Requirements/black Box +1	Any	Differential privacy provides mathematically rigorous privacy protection by adding carefully calibrated random noise to...
Quantile Regression	Algorithmic	Architecture/linear Models/regression Architecture/neural Networks +4	Any	Quantile regression estimates specific percentiles (quantiles) of the target variable rather than just predicting the...
Conformal Prediction	Algorithmic	Architecture/model Agnostic Requirements/black Box	Any	Conformal prediction provides mathematically guaranteed uncertainty quantification by creating prediction sets that...
Empirical Calibration	Algorithmic	Architecture/model Agnostic Paradigm/supervised +2	Any	Empirical calibration adjusts a model's predicted probabilities to match observed frequencies. For example, if events...
Temperature Scaling	Algorithmic	Architecture/neural Networks Paradigm/discriminative +3	Any	Temperature scaling adjusts a model's confidence by applying a single parameter (temperature) to its predictions. When a...
Bootstrapping	Algorithmic	Architecture/model Agnostic Paradigm/supervised +2	Any	Bootstrapping estimates uncertainty by repeatedly resampling the original dataset with replacement to create many new...
Jackknife Resampling	Algorithmic	Architecture/model Agnostic Paradigm/supervised +2	Any	Jackknife resampling (also called leave-one-out resampling) assesses model stability and uncertainty by systematically...
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...
Neuron Activation Analysis	Algorithmic	Architecture/neural Networks Requirements/model Internals +1	Text	Neuron activation analysis examines the firing patterns of individual neurons in neural networks by probing them with...
Feature Attribution with Integrated Gradients in NLP	Algorithmic	Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +4	Text	Applies Integrated Gradients to natural language processing models to attribute prediction importance to individual...

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