Explainability
Data Patterns
Uncovers underlying structures and relationships in data
11 techniques in this subcategory
11 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Partial Dependence Plots | Algorithmic | Architecture/model Agnostic Requirements/black Box | Any | Partial Dependence Plots show how changing one or two features affects a model's predictions on average. The technique... | ||
| Individual Conditional Expectation Plots | Visualization | Architecture/model Agnostic Requirements/black Box | Any | Individual Conditional Expectation (ICE) plots display the predicted output for individual instances as a function of a... | ||
| Factor Analysis | Algorithmic | Architecture/model Agnostic Paradigm/unsupervised +1 | Tabular | Factor analysis is a statistical technique that identifies latent variables (hidden factors) underlying observed... | ||
| Principal Component Analysis | Algorithmic | Architecture/model Agnostic Paradigm/unsupervised +1 | Any | Principal Component Analysis transforms high-dimensional data into a lower-dimensional representation by finding the... | ||
| t-SNE | Visualization | Architecture/model Agnostic Requirements/black Box | Any | t-SNE (t-Distributed Stochastic Neighbour Embedding) is a non-linear dimensionality reduction technique that creates 2D... | ||
| UMAP | Visualization | Architecture/model Agnostic Requirements/black Box | Any | UMAP (Uniform Manifold Approximation and Projection) is a non-linear dimensionality reduction technique that creates 2D... | ||
| 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... | ||
| 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... | ||
| 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... | ||
| Attention Visualisation in Transformers | Algorithmic | Architecture/neural Networks/transformer Requirements/architecture Specific +1 | Image Text | Attention Visualisation in Transformers analyses the multi-head self-attention mechanisms that enable transformers to... |
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