Some examples and use cases from the internet:

Some examples and use cases from the internet:

• returns the network's output value y = y(x) for an input value x = 0.5. To calculate the Jacobian Matrix of the network in response to an input Vector we use.
• Supervised learning, on the other hand, requires the discrepancy between the network's output value and the target (desired output) value to be measured.
• a lower density around the point representing a perfectly symmetric face. The network's output value at that point still could be slightly smaller than the ones of  ...
• We compare the network's output value against the desired value in terms of the partial derivative of P = –1/2(d–o)2 with respect to particular weights wi. This is ...

• 1: A subset of training samples is presented to the network. The output of the neurons is computed using following equations  ...
• Batch training: the whole set of samples is presented to the network and winner neurons are found; after this, the map weights are updated with the effect of all ...
• fixed number of training samples is presented to the network, after which the test set is presented to the network and the generalization ability of the network is ...
• When the batch training is used, the whole set of samples is presented to the network and winner neurons are found; after this, the map weights are updated with ...
• ... Back Propagation Algorithm Step