Proceedings of the First International Conference on Information Science and Electronic Technology

Adaptive Data Mining Algorithm under the Massive Data

Authors
Weijian Mo
Corresponding Author
Weijian Mo
Available Online March 2015.
DOI
https://doi.org/10.2991/iset-15.2015.10How to use a DOI?
Keywords
Neural networks, Data mining, Clustering, Rule extraction
Abstract
In order to solve the problem that Network Reduced accuracy and poor convergence in the existing neural network, which because sample large volumes of data and target data-independent. In response to this phenomenon, this paper put forward a data mining based on compensatory fuzzy neural network. It was optimizing was the Compensative Fuzzy Neural Network. And improve the cutting effect base on calculation algorithm. At the end, it was based on the similarity of each cluster objects to clustering process the system data. Through simulation experiments we can see, algorithm can maintain high precision under different circumstances the amount of data. Compared to other algorithms, we can see that it has a large advantage in terms of both accuracy and time-consuming.
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Proceedings
First International Conference on Information Science and Electronic Technology (ISET 2015)
Part of series
Advances in Computer Science Research
Publication Date
March 2015
ISBN
978-94-62520-50-9
DOI
https://doi.org/10.2991/iset-15.2015.10How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Weijian Mo
PY  - 2015/03
DA  - 2015/03
TI  - Adaptive Data Mining Algorithm under the Massive Data
BT  - First International Conference on Information Science and Electronic Technology (ISET 2015)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iset-15.2015.10
DO  - https://doi.org/10.2991/iset-15.2015.10
ID  - Mo2015/03
ER  -