Improved FP Growth Algorithm for Mining Association Rules

Name: Improved FP Growth Algorithm for Mining Association Rules
Brand: LAP Lambert Academic Publishing
SKU: 9783330341906
Price: 710 CZK
Availability: InStock

Autor: Kuldeep Singh, Saroj Dahiya Ratnoo

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP Lambert Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 8-11 dnů

710 Kč

Mining frequent patterns (itemsets) plays an important role of in discovering association rules. How...

Informace o knize

Autor

Kuldeep Singh, Saroj Dahiya Ratnoo

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2017

Stránek

EAN

9783330341906

Enbook ID

16819230

Vydavatel

LAP Lambert Academic Publishing

Hmotnost

102

Rozměry

150 x 220 x 3

Kompletní popis

Mining frequent patterns (itemsets) plays an important role of in discovering association rules. However, finding frequent itemsets is most expensive step in the process of association rule mining. Very often algorithms to find frequent itemsets need multiple database scans creating a bottle-neck to achieve efficiency. To avoid this bottle-neck the objective has been to reduce database scans. In the past, Apriori-like methods were adopted to mine frequent itemsets. But these approaches are inefficient as they require multiple database scans and iteratively check a large set of candidates by pattern matching. A compact structure, called FP-Tree, was developed to improve the disadvantages of Apriori-like algorithms. By FP-Growth approach, we can facilitate mining frequent itemsets. This book proposes an Improved FP-Growth algorithm that scans database only once for association rule mining. The original FP-Growth algorithm scans datasets twice. First time, scanning database to find the frequent 1-itemsets, and sorting the 1-itemsets in the descending order of support and second time it scans the database again to construct FP-tree.

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Improved FP Growth Algorithm for Mining Association Rules

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