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MaPle: Efficient Enumeration of δ-pClusters
- Pei et al., MaPle: Efficient enumerating all maximal δ-pClusters. ICDM'03
- Framework: Same as pattern-growth in frequent pattern mining (based on the downward closure property)
- For each condition combination J, find the maximal subsets of genes I such that I x J is a δ-pClusters
- If I x J is not a submatrix of another δ-pClusters
- then I x J is a maximal δ-pCluster.
- Algorithm is very similar to mining frequent closed itemsets
- Additional advantages of δ-pClusters:
- Due to averaging of δ-cluster, it may contain outliers but still within δ-threshold
- Computing bi-clusters for scaling patterns, take logarithmic on
- will lead to the p-score form
\[\frac{d_{xa}/d_{ya}}{d_{xb}/d_{yb}}<\delta \]
Speaker notes:
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