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V13 (642-645): PR: Stock Prophet, version 2.0 by John Sweeney
V13 (642-645): PR: Stock Prophet, version 2.0 by John Sweeney
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$4.95 USD
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$4.95 USD
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Stock Prophet Version 2.0 by John Sweeney
Stock Prophet from Future Wave Software is a data preprocessor and technical analysis package for use with neural network development software.
Future Wave Software's Stock Prophet is a studious program that preprocesses trading indicators for use in neural network trading systems. What is data preprocessing? It's taking your raw data, transforming it (into, say, indicators), then compressing and aligning it into comparable periods. Then you scale it into values between zero and one so that the neural network algorithm has the right variables properly presented when it starts estimating neuron weights. Preprocessing also includes smoothing, detrending and selecting the best indicators for the selected market.
Previously, preprocessing data was the bane of using neural networks for trading. When neural network programs first became popular with traders, most software left the chore of data preprocessing up to the user. You would usually perform the preprocessing in spreadsheets, whence you would dump out an ASCII file that the neural network program could read. File formatting being the tedious, error-prone problem it is, this process could result in lots of frustration and numerous calls to technical support.
Stock Prophet from Future Wave Software is a data preprocessor and technical analysis package for use with neural network development software.
Future Wave Software's Stock Prophet is a studious program that preprocesses trading indicators for use in neural network trading systems. What is data preprocessing? It's taking your raw data, transforming it (into, say, indicators), then compressing and aligning it into comparable periods. Then you scale it into values between zero and one so that the neural network algorithm has the right variables properly presented when it starts estimating neuron weights. Preprocessing also includes smoothing, detrending and selecting the best indicators for the selected market.
Previously, preprocessing data was the bane of using neural networks for trading. When neural network programs first became popular with traders, most software left the chore of data preprocessing up to the user. You would usually perform the preprocessing in spreadsheets, whence you would dump out an ASCII file that the neural network program could read. File formatting being the tedious, error-prone problem it is, this process could result in lots of frustration and numerous calls to technical support.
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