Then the error at the hidden nodes is calculated (by back-propagating the error at the output units through the weights), forex trading making a living and the weights on the hidden nodes altered using these values. Step 3: Output nodes calculate their outputs on the basis of Step 2.
Step 4: Calculate the differences between the results of Step 3 and targets. Step 5: Apply the first part of the training rule using the results of Step 4.
(derivative) Step 7: Apply the second part of the training rule using the results of Step 6. Steps 1 through 3 are often called the forward pass , and steps 4 through 7 are often called the backward pass. For each data pair to be learned a forward pass and backwards pass is performed.
This is repeated over and over again until the error is at a low enough level (or we give up). You may refer to this link for a complete tutorial on neural network. Stock market prediction Credit card fraud detection Cancer diagnosis Economic forecasting Optimization Lottery prediction Credit hedge forex robot review worthiness Etc.
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