[kimageprocess-devel] kimageprocess/src/plugins/fann fann.cpp fann.h

[Gustavo P. B. <gb...@us...>]

Update of /cvsroot/kimageprocess/kimageprocess/src/plugins/fann
In directory sc8-pr-cvs1.sourceforge.net:/tmp/cvs-serv23715/fann

Modified Files:
	fann.cpp fann.h 
Log Message:
- Use less iterations (50k)
- Use two hidden layers by default
- Using FANN_TRAIN_BATCH algorith



Index: fann.h
===================================================================
RCS file: /cvsroot/kimageprocess/kimageprocess/src/plugins/fann/fann.h,v
retrieving revision 1.6
retrieving revision 1.7
diff -u -d -r1.6 -r1.7
--- fann.h	3 Jul 2005 02:14:33 -0000	1.6
+++ fann.h	8 Jul 2005 20:05:54 -0000	1.7
@@ -59,6 +59,7 @@
     float m_steepnessOutput;
     int m_iterations;
     float m_desiredError;
+    unsigned int m_trainingAlgorithm;
 };
 
 #endif

Index: fann.cpp
===================================================================
RCS file: /cvsroot/kimageprocess/kimageprocess/src/plugins/fann/fann.cpp,v
retrieving revision 1.12
retrieving revision 1.13
diff -u -d -r1.12 -r1.13
--- fann.cpp	6 Jul 2005 01:34:43 -0000	1.12
+++ fann.cpp	8 Jul 2005 20:05:54 -0000	1.13
@@ -36,12 +36,13 @@
  : KTClassifBackend(parent, name)
 {
     m_network = 0;
-    m_iterations = 300000;
-    m_hiddenLayers = 1;
+    m_iterations = 50000;
+    m_hiddenLayers = 2;
     m_connectionRate = 1.0;
     m_learningRate = 0.7;
     m_activationFunctionHidden = FANN_SIGMOID_SYMMETRIC;
     m_activationFunctionOutput = FANN_SIGMOID_SYMMETRIC;
+    m_trainingAlgorithm = FANN_TRAIN_BATCH;
     m_steepnessHidden = 1.0;
     m_steepnessOutput = 1.0;
     m_desiredError = 0.0001;
@@ -71,6 +72,10 @@
     fann_set_activation_function_hidden(m_network, m_activationFunctionHidden);
     fann_set_activation_function_output(m_network, m_activationFunctionOutput);
 
+    fann_set_training_algorithm(m_network, m_trainingAlgorithm);
+    
+    fann_print_parameters(m_network);
+
     struct fann_train_data fanndata;
     float *in, *out;
     int n = data.count();
@@ -103,7 +108,7 @@
         c++;
     }
     fann_init_weights(m_network, &fanndata);
-    fann_train_on_data(m_network, &fanndata, m_iterations, m_iterations / 100, m_desiredError);
+    fann_train_on_data(m_network, &fanndata, m_iterations, 500, m_desiredError);
 
     //clear data
     delete in;