Optimization Analysis of Neural Network Algorithms Using Bagging Techniques on Classification of Date Fruit Types
R Pramudita, N Safitri - 2022 Seventh International …, 2022 - ieeexplore.ieee.org
2022 Seventh International Conference on Informatics and Computing …, 2022•ieeexplore.ieee.org
To perform an optimization One of the machine learning algorithms is by using Ensemble
Learning. The main problem in this study is to increase the accuracy of the neural network
algorithm in classifying data. This study aims to optimize the neural network algorithm in
classifying. There are many optimization algorithms in classifying. In this study, we tried to
optimize using the bagging technique for classification. This study uses types of dates as a
case study. The results of the model evaluation show that the neural network algorithm plus …
Learning. The main problem in this study is to increase the accuracy of the neural network
algorithm in classifying data. This study aims to optimize the neural network algorithm in
classifying. There are many optimization algorithms in classifying. In this study, we tried to
optimize using the bagging technique for classification. This study uses types of dates as a
case study. The results of the model evaluation show that the neural network algorithm plus …
To perform an optimization One of the machine learning algorithms is by using Ensemble Learning. The main problem in this study is to increase the accuracy of the neural network algorithm in classifying data. This study aims to optimize the neural network algorithm in classifying. There are many optimization algorithms in classifying. In this study, we tried to optimize using the bagging technique for classification. This study uses types of dates as a case study. The results of the model evaluation show that the neural network algorithm plus the bagging technique produces an accuracy rate of 96%, and this has a higher accuracy of 1% compared to the neural network algorithm alone.
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