<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to update the population, the algorithm increases the convergence speed and enhances the searching ability, compared to GA. In the experiment of mining association, rules in blood indices data, PBIL algorithm performs better not only in running time, convergence speed, but also achieve better searching results. Meanwhile, this paper proposed a parallel algorithm for association rule mining based on PBIL and designed a system architecture based on cloud computing for blood indices analysis, providing a good example to apply the new algorithm to cloud computing.</p>
</abstract>

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to update the population, the algorithm increases the convergence speed and enhances the searching ability, compared to GA. In the experiment of mining association, rules in blood indices data, PBIL algorithm performs better not only in running time, convergence speed, but also achieve better searching results. Meanwhile, this paper proposed a parallel algorithm for association rule mining based on PBIL and designed a system architecture based on cloud computing for blood indices analysis, providing a good example to apply the new algorithm to cloud computing.

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association...

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

Data publikacji: 10 kwi 2018

Zakres stron: 20 - 26

DOI: https://doi.org/10.21307/ijanmc-2017-087

Słowa kluczowe
Distribution estimation algorithm, Probability vector, Blood indices, Parallel algorithm, Cloud computing

© 2017 Xinyu Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

Data publikacji: 10 kwi 2018

Zakres stron: 20 - 26

DOI: https://doi.org/10.21307/ijanmc-2017-087

Słowa kluczoweDistribution estimation algorithm, Probability vector, Blood indices, Parallel algorithm, Cloud computing

© 2017 Xinyu Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
Distribution estimation algorithm, Probability vector, Blood indices, Parallel algorithm, Cloud computing