Explainability
Feature Relationships
Visualises how features affect predictions (e.g., PDP, ICE Plots)
4 techniques in this subcategory
4 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... | ||
| 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... | ||
| 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... |
Rows per page
Page 1 of 1