Exercise:Softmax Regression

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(Step 3: Gradient checking)
(Step 0: Initialise constants and parameters)
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In the file <tt>[http://ufldl.stanford.edu/wiki/resources/softmax_exercise.zip softmax_exercise.zip]</tt>, we have provided some starter code. You should write your code in the places indicated by "YOUR CODE HERE" in the files. You will need to modify <tt>softmaxCost.m</tt> and <tt>softmaxPredict.m</tt> for this exercise.
In the file <tt>[http://ufldl.stanford.edu/wiki/resources/softmax_exercise.zip softmax_exercise.zip]</tt>, we have provided some starter code. You should write your code in the places indicated by "YOUR CODE HERE" in the files. You will need to modify <tt>softmaxCost.m</tt> and <tt>softmaxPredict.m</tt> for this exercise.
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=== Step 0: Initialise constants and parameters ===
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=== Step 0: Initialize constants and parameters ===
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Two constants, <tt>inputSize</tt> and <tt>outputSize</tt>, corresponding to the size of each input vector and the number of class labels have been defined in the starter code. This will allow you to reuse your code on a different data set in a later exercise. We also initialise <tt>lambda</tt>, the weight decay parameter here.
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Two constants, <tt>inputSize</tt> and <tt>outputSize</tt>, corresponding to the size of each input vector and the number of class labels have been defined in the starter code. This will allow you to reuse your code on a different data set in a later exercise. We also initialize <tt>lambda</tt>, the weight decay parameter here.
=== Step 1: Load data ===
=== Step 1: Load data ===

Revision as of 01:13, 6 May 2011

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