This commit is contained in:
Gustav Louw 2018-04-10 19:24:15 -07:00
parent 10eb871ca7
commit 84d24b97a3
2 changed files with 24 additions and 3 deletions

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@ -82,7 +82,7 @@ At the end of the line 10 digits signify the digit:
This gives 10 outputs to the neural network. The test program will output the
accuracy for each digit. Expect above 99% accuracy for the correct digit, and
less that 1% accuracy for the other digits.
less that 0,1% accuracy for the other digits.
# Tips

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