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Artificial neural networks (ANN), are composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows information to propagate through the network to solve artificial intelligence problems without the network designer having had a model of a real system.
0
votes
1
answer
268
views
Encog neural network multiple outputs
I am a little confused with using encog to create a neural network.
I am trying text classification with a basic feed forward network. For the input data I have 200 unique words (features/inputs) to …
0
votes
1
answer
263
views
Text classification with neural network number of input neurons
I am classifying documents I have around 4000 of them that I am trying to categorise into 5 categories. I am using a bag of words model which equates to about 18,000 unique words (features) and theref …
1
vote
Accepted
Encog neural network multiple outputs
Needed to normalise the data which encodes the column and then denormalise on the output which gives the correct classification.
4
votes
1
answer
5k
views
One hot encoding vs Word embedding
I am very confused between one hot encoding and word embedding in terms of structure of the network and how it reduces the dimensionality.
I am currently using encog with c# which has some documentati …