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https://github.com/glouw/tinn
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cleanup
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@ -82,7 +82,7 @@ At the end of the line 10 digits signify the digit:
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This gives 10 outputs to the neural network. The test program will output the
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accuracy for each digit. Expect above 99% accuracy for the correct digit, and
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less that 1% accuracy for the other digits.
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less that 0,1% accuracy for the other digits.
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# Tips
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25
test.c
25
test.c
@ -1,3 +1,26 @@
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// gcc test.c Tinn.c -lm
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//
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// Tinn does not include functionality for loading
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// and parsing data sets as all data sets are different.
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//
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// This example shows how to open an example data file from the machine learning archives.
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// The training data consists of hand written digits and can be found at:
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//
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// http://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data
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//
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// Each line is one digit. A digit consists of 256 pixels (16 x 16 display).
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// Each line finishes with 10 digits indicating the digit:
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//
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// 0: 1 0 0 0 0 0 0 0 0 0
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// 1: 0 1 0 0 0 0 0 0 0 0
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// 2: 0 0 1 0 0 0 0 0 0 0
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// 3: 0 0 0 1 0 0 0 0 0 0
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// 4: 0 0 0 0 1 0 0 0 0 0
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// ...
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// 9: 0 0 0 0 0 0 0 0 0 1
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//
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// This gives 256 inputs and 10 outputs to the neural network.
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#include "Tinn.h"
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#include <stdio.h>
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#include <time.h>
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@ -125,8 +148,6 @@ static Data build(const char* path, const int nips, const int nops)
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return data;
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}
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// This example learns hand written digits.
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// Be sure to first get the training data from http://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data
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int main()
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{
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// Tinn does not seed the random number generator.
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