kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets

We have presented the Partial Counting algorithm for mining frequent item- sets from data streams with a space complexity proportional to the number of frequent itemsets generated

“If we constructed two similar strips, and if we put the second one behind the first one returning it and making correspond 1 cell with 2n cell, it is evident that if Goldbach

In fact, they browse the search space by traversing the lattice of frequent itemsets from an equivalence class to another, and they calculate the closure of the frequent

Given a sample of binary random vectors with i.i.d. 1 − p), we first establish a formula for the mean of the size of the random Galois lattice built from this sample, and a more

Multivariate Student, also called t-distributions, are useful when dealing with real-data because of their heavy tails. They are a robust alternative to the Gaussian distribution,

Treatment with pertuzumab (24 h) led to HER3 protein increase, which could be involved in bypassing the pertuzumab-induced HER2 inhibition, as observed by Garrett et al [24]

Une correction de biais est alors nécessaire : elle est obtenue, pour chaque secteur d'activité (en NES16 et NES36), par un étalonnage de l'indicateur sur les estimations

In this paper, we proposes the ClosedPattern global constraint to capture the closed frequent pattern mining problem without requiring reified constraints or extra variables..