An Unsupervised Neural Network for Stock Prediction
نویسندگان
چکیده
The unsupervised Kohonen Networks equipped with Short Term Memory and Random Walk Breakout are used with straight-line equation as the curve fitting algorithm to predict the stock prices. According to the results obtained, the unsupervised networks do not have that high accuracy of prediction in general because of the constraint on the fixed number of patterns that they can recognize. However, they provide the fastest time output and thus are very useful in time critical situations.
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