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: 12095 HUF
Availability: InStock

Szerző: Kuldeep Singh, Saroj Dahiya Ratnoo

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Kötés: Puha kötésű

Kiadó: LAP Lambert Academic Publishing

Elérhetőség: Beszállítói készleten

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

Információk a könyvről

Szerző

Kuldeep Singh, Saroj Dahiya Ratnoo

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2017

oldal

EAN

9783330341906

Enbook ID

16819230

Kiadó

LAP Lambert Academic Publishing

Súly

102

Méretek

150 x 220 x 3

Teljes leírás

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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