Explainability
Sparsity
Focuses on few, most important factors
10 techniques in this subcategory
10 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Gradient-weighted Class Activation Mapping | Algorithmic | Architecture/neural Networks/convolutional Requirements/architecture Specific +3 | Image | Grad-CAM (Gradient-weighted Class Activation Mapping) draws a heatmap over an image showing which regions most raise a... | ||
| Occlusion Sensitivity | Algorithmic | Architecture/model Agnostic Requirements/black Box | Image | Occlusion sensitivity shows which parts of an input a model's prediction is sensitive to. A region of the input, such as... | ||
| Prototype and Criticism Models | Algorithmic | Architecture/model Agnostic Paradigm/supervised +2 | Any | Prototype and criticism methods summarise a dataset with a small set of real examples. Prototypes are instances chosen... | ||
| Contrastive Explanation Method | Algorithmic | Architecture/neural Networks Paradigm/discriminative +4 | Any | The Contrastive Explanation Method (CEM) explains one prediction of a classifier, such as a neural network, by... | ||
| ANCHOR | Algorithmic | Architecture/model Agnostic Requirements/black Box | Tabular | ANCHOR explains one prediction of a black-box classifier with an if-then rule, called an anchor, such as 'age > 30 AND... | ||
| RuleFit | Algorithmic | Architecture/model Agnostic Paradigm/supervised +1 | Tabular | RuleFit builds a predictive model that a person can read: a short list of if-then rules plus a few ordinary feature... | ||
| Generalized Additive Models | Algorithmic | Architecture/linear Models/gam Paradigm/parametric +2 | Tabular | A generalised additive model (GAM) builds its prediction by adding a baseline and one smooth curve for each input... | ||
| Diverse Counterfactual Explanations | Algorithmic | Architecture/model Agnostic Paradigm/supervised +1 | Tabular | Diverse Counterfactual Explanations (DiCE) explains one decision of a classifier by generating several altered versions... | ||
| GNNExplainer | Algorithmic | Architecture/neural Networks Requirements/gradient Access +2 | Graph | GNNExplainer explains one prediction of a graph neural network, a model that passes information along the edges of a... | ||
| Sparse Autoencoder Feature Analysis | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +2 | Text | Sparse autoencoder feature analysis looks for human-interpretable units inside a neural network, usually a language... |
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