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Neural Networks

  1. Feb 3, 2013 #1
    1. The problem statement, all variables and given/known data

    I am trying to train a neural network using the following training set:

    (4,6)
    (9,10)
    (1,2)
    (6,2)

    So, if I enter input 4, it should give me 6. If I enter 9, output should be 10.
    If I enter 3.5, it should approximate an output based on the training examples.

    2. Relevant equations

    weight update rule:

    w_new = w_old + (-learning rate) * (error) * (input)



    3. The attempt at a solution

    So, lets say I randomly initialize the weights and get w1 = 3 and w0 = 4

    For the first example,

    (4,6)

    The input will be (4,1) because of the intercept.

    4*3 + 4*1 = 16

    The difference between the target value and the actual output is 10.

    Now, I just need help with the weight update rule because I am not sure how to proceed.

    For example:

    Can I subtract 4 from the error because of the intercept to get error = 6
    learning rate = -.1
    w_new = 3 + (-.1)*(6)*(4)
    w_new = .6

    Then to test this I get:
    4*.6 + 4*1 = 6.4

    Any help greatly appreciated!
     
  2. jcsd
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