Algorithms for Large Scale Markov Blanket Discovery.¶
Tsamardinos, I., Aliferis, C. F., & Statnikov, A. (2003). Algorithms for Large Scale Markov Blanket Discovery. Proceedings of the 16th International FLAIRS Conference, 376-380.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Markov Blanket
- In machine-learning feature selection and causal discovery, a target's blanket is the smallest sufficient feature set — adding outside features cannot improve predictions, removing blanket features must hurt them — which algorithms like IAMB and MMMB operationalize.
This sourcePresents IAMB and related algorithms identifying a target's Markov blanket as its smallest sufficient feature set for classification and causal discovery.
- In machine-learning feature selection and causal discovery, a target's blanket is the smallest sufficient feature set — adding outside features cannot improve predictions, removing blanket features must hurt them — which algorithms like IAMB and MMMB operationalize.
Verification¶
This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.
Registry ID ref:171eefd3cc24 · see in the full table