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Role of Artificial Neural Network in Data Mining


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1 Guru Jambeshwar University Science and Technology, Hisar, Haryana, India
     

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Neural networks have emerged as advanced data mining tools in cases where other techniques may not produce satisfactory predictive models. As the term implies, neural networks have a biologically inspired modelling capability but are essentially statistical modelling tools. Artificial neural networks is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. Artificial Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques that could help in Decision-making .Neural Networks have been successfully applied in a wide range of supervised and unsupervised learning applications. ANN methods are not commonly used for data-mining tasks, because they may have complex structure,long training time, and uneasily understandable representation of results& often produce incomprehensible models. However, artificial neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining.

Keywords

Artificial Neural Network (ann), Neural Network Topology Data Mining, Data Warehousing.
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  • Role of Artificial Neural Network in Data Mining

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Authors

Jyoti Goyat
Guru Jambeshwar University Science and Technology, Hisar, Haryana, India
Sakshi Dhingra
Guru Jambeshwar University Science and Technology, Hisar, Haryana, India
Vinod Goyal
Guru Jambeshwar University Science and Technology, Hisar, Haryana, India

Abstract


Neural networks have emerged as advanced data mining tools in cases where other techniques may not produce satisfactory predictive models. As the term implies, neural networks have a biologically inspired modelling capability but are essentially statistical modelling tools. Artificial neural networks is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. Artificial Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques that could help in Decision-making .Neural Networks have been successfully applied in a wide range of supervised and unsupervised learning applications. ANN methods are not commonly used for data-mining tasks, because they may have complex structure,long training time, and uneasily understandable representation of results& often produce incomprehensible models. However, artificial neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining.

Keywords


Artificial Neural Network (ann), Neural Network Topology Data Mining, Data Warehousing.