I\'m using a feed-foward neural network in python using the pybrain implementation. For the training, i\'ll be using the back-propagation algorithm. I know that with the neural-networks, we need to h
recently I came to study clustering in data-mining an开发者_运维技巧d I\'ve studied sequential clustering and hierarchical clustering and k-means.
I am attempting to train a neural network for a system that 开发者_StackOverflow中文版can be thought of as a macro-level postal network. My inputs are two locations (one of the 50 US states) along wit
EDIT2: New training set... Inputs: [ [0.0, 0.0], [0.0, 1.0], [0.0, 2.0], [0.0, 3.0], [0.0, 4.0], [1.0, 0.0],
I am currently searching for a neural network (toy) example, that I might optimize using GPU kernels. I need
I\'m trying to add to the code for a single layer neural network which takes a bitmap as input and has 26 outputs for the likelihood of each letter in the alphabet.
I have a very simple linear classification problem,which is to work out a linear classification problem for the following three classes in coordinates:
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Same length 5 metal rods has a hole (of same diameter) in different places. Using neural network we have to detect where the hole is by using sound produced when the metal rod is knocked.
do you know any good set of training images for my test neural network preferably a tagged set of images of numb开发者_开发问答ers or letters
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