applicable models
tree based
Techniques for tree-based algorithms (decision trees, random forests, gradient boosting)
4 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Mean Decrease Impurity | Algorithmic | Architecture/tree Based Paradigm/supervised +1 | Tabular | Mean Decrease Impurity (MDI) scores how much each feature contributes to a tree-based model, such as a random forest, by... | ||
| Homomorphic Encryption | Algorithmic | Architecture/linear Models Architecture/model Agnostic +5 | Any | Homomorphic encryption lets a server compute on data that stays encrypted, so the server never sees the underlying... | ||
| Monotonicity Constraints | Algorithmic | Architecture/neural Networks Architecture/probabilistic/gaussian Processes +3 | Tabular | Monotonicity constraints require a model's prediction to move only one way as a chosen input rises, with the other... | ||
| Zero-Knowledge Proof of Model Inference | Algorithmic | Architecture/neural Networks Architecture/tree Based +1 | Any | A zero-knowledge proof of model inference lets the owner of a model show an outside party that one specific model, fixed... |
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