Prueba de Conocimiento Cero
Probar sin revelar.
Properties: 1. No child pointers. 2. Degree = 1 (in undirected trees). 3. Terminal state. 4. Base case for recursion.
graph LR
Center["Prueba de Conocimiento Cero"]:::main
Rel_zero_knowledge_proofs_zkps["zero-knowledge-proofs-zkps"]:::related -.-> Center
click Rel_zero_knowledge_proofs_zkps "/terms/zero-knowledge-proofs-zkps"
Rel_zero_knowledge_proof["zero-knowledge-proof"]:::related -.-> Center
click Rel_zero_knowledge_proof "/terms/zero-knowledge-proof"
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classDef pre fill:#0f172a,stroke:#3b82f6,color:#94a3b8,rx:5,ry:5;
classDef child fill:#0f172a,stroke:#10b981,color:#94a3b8,rx:5,ry:5;
classDef related fill:#0f172a,stroke:#8b5cf6,stroke-dasharray: 5 5,color:#94a3b8,rx:5,ry:5;
linkStyle default stroke:#4b5563,stroke-width:2px;
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🤓 Expert Deep Dive
Technically, in graph theory, a leaf is a vertex of degree 1. In a rooted tree, it is a node with an out-degree of zero. Leaf nodes are the 'Base Case' for most recursive algorithms. For example, in a 'Minimax' algorithm used in game AI, the evaluation function is only called when the search reaches a leaf node (a terminal state of the game). In 'B-Trees' (used in databases), data is often stored exclusively in leaf nodes to ensure that all lookups take the same amount of time. 'Pruning' is the process of removing leaf nodes to simplify a model, which is a key technique in Machine Learning to prevent 'Overfitting'.