Explainability
Visualization Methods
Techniques focused on visual representation of model behavior
3 subcategories • 7 techniques
Activation Maps
Creates visual heatmaps of model activations (e.g., Grad-CAM)
Attention Patterns
Displays attention mechanisms in models (e.g., Attention Weight Analysis)
Feature Relationships
Visualises how features affect predictions (e.g., PDP, ICE Plots)
Techniques
7 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Partial Dependence Plots | Visualisation | Architecture/model Agnostic Requirements/black Box | Tabular | Partial Dependence Plots show how changing one or two features affects a model's predictions on average. The technique... | ||
| Individual Conditional Expectation Plots | Visualisation | Architecture/model Agnostic Requirements/black Box | Tabular | Individual Conditional Expectation (ICE) plots display the predicted output for individual instances as a function of a... | ||
| t-SNE | Algorithmic | Architecture/model Agnostic Requirements/black Box | Any | t-SNE (t-distributed Stochastic Neighbour Embedding) turns high-dimensional data into a two- or three-dimensional map... | ||
| 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... | ||
| Gradient Saliency | Algorithmic | Architecture/neural Networks Requirements/differentiable +2 | Image | Gradient saliency (also called vanilla gradient saliency) is the simplest gradient-based explanation for image... | ||
| 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... | ||
| Attention Weight Analysis | Algorithmic | Architecture/neural Networks/recurrent Architecture/neural Networks/transformer +2 | Image Text | Attention weight analysis reads the weights an attention-based neural network assigns to the parts of its input, to see... |
Rows per page
Page 1 of 1