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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 …
Simon Nicholls's user avatar
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 …
Simon Nicholls's user avatar
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.
Simon Nicholls's user avatar
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 …
Simon Nicholls's user avatar