Introduction to NeuNet Pro |
Introduction What is Neural Net? Suggested Uses SFAM Classification Back Propagation NeuNet Overview |
Back Propagation Neural NetworksBack Propagation (BackProp) is the most common type of neural network. The algorithm was provided and popularized by Rumelhart, Hinton and Williams in 1986, following work by Parker, LeCun, Werbos and Rosenblatt. BackProp makes its predictions as numeric values, not as class names. BackProp is well suited for predicting continuous numerical values such as prices, weights and times. BackProp can also be used for classification problems, where each class is assigned a numeric value. The following points reflect our thoughts after several years experience using BackProp.
BackProp Strengths:
BackProp Weaknesses:
A Typical BackProp Neural Network(Used For Predicting Values)
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A Complete Neural Network Development System |