Sampling in Data Mining

Weiß, Christian

doi:10.1002/9781118445112.stat04222.pub2

Cited by 1 publication

(1 citation statement)

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“…One of the changes to the Apriori algorithm is the passing reduction on databases [12]. In another method, sampling is used instead of examining the entire database [13]. Also, the use of parallel algorithms to discover the association rules is proposed and investigated in [14].…”

Section: Related Workmentioning

confidence: 99%

Geographic data-mining and extraction of association rules using the Apriori algorithm (Case study: Capital of Iranian provinces)

Houshmand-Nanehkaran

Lajevardi

Mahlouji-Bidgholi

2021

Preprint

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Extracting of association rules between urban features provides latent and considerable information for urban planners about the relationships between urban characteristics and their similarities. For this purpose, in this paper, the most famous and well-known Apriori algorithm is used. We present the Fariori algorithm to delay the characteristics that can be deleted during execution, as well as to achieve main and frequent features in the early stages with efficient changes to the Apriori algorithm. Although the spatial and temporal complexity of both algorithms is exponential based on the number of fea-tures, in practice, by implementing the Fariori algorithm in MATLAB, we achieved more rules than the existing software (R, Weka, Market Basket Analysis and, Yarpiz). In the proposed algorithm, it is possible to determine the degree of similarity by adjust-ing the support and confidence ratio parameters to identify a coherent set of similar cities. The used database includes cities of 31 in the provincial capitals of Iran. Dis-covering the association rules leads to similar cities finding and can be an efficient aid in the decision-making process.

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Section: Related Workmentioning

confidence: 99%