I have this code about neural networks. How can I modify this code so that it can show the training and testing graphs?
Ok, so this question is related to my ongoing task of getting text data categorized, you can refer to this question for more details on how I approached this problem.
Example: I have 20 persons as object, and every person knows 0-n others. The direction of the link matters! A person A might know B, but B might not know A. It\'s a directed graph.
I\'m currently working on a Neural Network for creating a \"better\" PNG Predictor (Prefilter). I already create开发者_开发知识库d the network (with JavaNNS) which has a quite good learning rate on 8
I have a supervised learning problem where my algorithm will be 开发者_StackOverflow中文版given a set of training examples for learning whether a shape is a circle of square.I was wondering which type
Is a neural network a lazy or eager learning method?Different web pages say different things so I want to get a solid answer with good literature to bac开发者_开发技巧k it up.The most obvious book to
I want to create an artificial neural network (in PyBrain) that follows the following layout: However, I cannot find the proper way to achieve this. The only option that I see in the documentation
I\'m currently using Neuroph to build a network to evaluate complex logical expressions. The method is called CIL2P for anyone interested and the method generates semi-recurrent networks (only recurs
I want the network to stop training when the bit fail is 0. When that normally happens, the desired error is pretty low. But If I set the desired error too low, the network 开发者_StackOverflowwill ke
So, for larger networks with large data sets, they take a while to train.It would be awesome if there was a way to share the computing time across multiple machines. However, the issue with that is th
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