Decision tree performance enhancement using an artificial neural network implementation1 1This work was supported in part by NSF grant IRI-9002087

1991 ◽  
pp. 71-88 ◽  
Author(s):  
Ishwar K. Sethi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Decision Tree ◽  
Performance Enhancement ◽  
Artificial Neural ◽  
Tree Performance

Timescale Ensemble Performance Enhancement through use of Artificial Neural Network

2019 ◽  
Vol 29 (S1) ◽  
pp. 478-488
Author(s):  
Shikha Maharana ◽  
Aakanksha Avnish Bhardwajan ◽  
T Subramanya Ganesh ◽  
B N Ramakrishna
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Performance Enhancement ◽  
Ensemble Performance ◽  
Artificial Neural

Data mining of digital phytosanitary

2021 ◽  
Author(s):  
T. Z. Ibragimov ◽  
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Artificial Neural Network ◽  
Decision Tree ◽  
Bayesian Classifier ◽  
Design Parameters ◽  
Data Set ◽  
Septoria Leaf Blotch ◽  
Leaf Blotch ◽  
Artificial Neural

methods of data mining were used to predict the Septoria leaf blotch of wheat. A system has been developed that allows parallel forecasting with the same data set using the methods of an artificial neural network, a decision tree, and a naive Bayesian classifier. The system allows you to interactively adjust the design parameters for each of the methods, see the results obtained and evaluate their effectiveness.

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