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Comparison between extreme learning machine and wavelet neural networks in data classification

机译:数据分类中极端学习机与小波神经网络的比较

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Extreme learning Machine is a well known learning algorithm in the field of machine learning. It's about a feed forward neural network with a single-hidden layer. It is an extremely fast learning algorithm with good generalization performance. In this paper, we aim to compare the Extreme learning Machine with wavelet neural networks, which is a very used algorithm. We have used six benchmark data sets to evaluate each technique. These datasets Including Wisconsin Breast Cancer, Glass Identification, Ionosphere, Pima Indians Diabetes, Wine Recognition and Iris Plant. Experimental results have shown that both extreme learning machine and wavelet neural networks have reached good results.
机译:极端学习机是机器学习领域的知名学习算法。它是关于一个具有单隐藏层的馈送前进神经网络。它是一种极快的学习算法,具有良好的泛化性能。在本文中,我们的目标是将极端学习机与小波神经网络进行比较,这是一种非常使用的算法。我们使用了六个基准数据集来评估每个技术。这些数据集包括威斯康星素乳腺癌,玻璃鉴定,电离层,皮玛印第安人糖尿病,葡萄酒识别和鸢尾植物。实验结果表明,极端学习机和小波神经网络都达到了良好的效果。

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