Improved FP Growth Algorithm for Mining Association Rules

Language: English

Published by LAP LAMBERT Academic Publishing Jun 2017, 2017

3330341904 / 9783330341906

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This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

Seller Inventory # 9783330341906

Title
Improved FP Growth Algorithm for Mining Association Rules
Author
Kuldeep Singh
Publisher
LAP LAMBERT Academic Publishing Jun 2017
Publication year
2017
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3330341904
ISBN 13
9783330341906
Item weight
102 grams
Dimensions
220x150x4 mm

buchversandmimpf2000

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