data_mining:association_rules

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Association Rules Mining

Mining Algorithmen

  1. Apriori
    1. Naiv
    2. Multi-Dimensionale Association Rules
    3. Multi-Level Association Rules
      1. Alternative Variante
    4. Level Crossing association Rules
    5. Optimierung
      1. Direct Hashing and Pruning
      2. Sampling
      3. Apriori B
  2. FP-Tree
    1. Projected Databases

FP-Trees

Frequent-Pattern Trees “Divide and conquer”-Strategie

Phase 1

Aufgabe: Sortieren der Frequent Items Ausgangspunkt: Frequent Item List L=<c:4,f:4,a:3,b:3,m:3,p:3>

TID Items Sortierte häufige Items
1 f,a,c,d,h,i,m,p c,f,a,m,p
2 a,b,c,f,l,m,o c,f,a,b,m
3 b,c,h,j,o c,b
4 b,f,k,s,p f,b,p
5 a,f,c,e,l,p,m,n c,f,a,m,p
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  • Last modified: 2014/02/11 20:47
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