Unsupervised learning for financial forecasting.
IEEE Conference on Computational Intelligence for Financial Engineering and Economics CIFEr（1998）
摘要
An unsupervised neural based approach to financial forecasting is presented in this paper; its performance is compared with that from a statistical technique and two other standard neural network techniques. We show that the unsupervised network outperforms multilayer perceptrons, radial basis function network and a standard ARIMA model.
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关键词
neural network,predictive models,neural networks,arima model,unsupervised learning,performance,multilayer perceptron,negative feedback,differential equations,computational intelligence,radial basis function network,artificial neural networks
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