More improvements to NM

jeffheaton · Apr 15, 2012 · ee7a879 · ee7a879
1 parent cf9f17c
commit ee7a879
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Showing 3 changed files with 11 additions and 11 deletions.
diff --git a/encog-cmd/encog-cmd.vcxproj.user b/encog-cmd/encog-cmd.vcxproj.user
@@ -1,7 +1,7 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <LocalDebuggerCommandArguments>train c:\test\iris.eg c:\test\iris.egb /train:nm</LocalDebuggerCommandArguments>
+    <LocalDebuggerCommandArguments>train d:\test\iris.eg d:\test\iris.egb /train:nm</LocalDebuggerCommandArguments>
     <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
   </PropertyGroup>
 </Project>
diff --git a/encog-core/encog.h b/encog-core/encog.h
@@ -77,6 +77,11 @@ extern "C" {
 #define PARAM_MAXPOS		"MAXPOS"
 #define PARAM_MAXVEL		"MAXVEL"
 
+/* Nelder Mead */
+#define PARAM_STEP			"STEP"
+#define PARAM_KONVERGE		"KONVERGE"
+#define PARAM_REQMIN		"REQMIN"
+
 #define ENCOG_TYPE_NEURAL_NETWORK	1
 #define ENCOG_TYPE_DATA				2
 #define ENCOG_TYPE_PSO				3

diff --git a/encog-core/nm.c b/encog-core/nm.c
@@ -374,6 +374,7 @@ static void _nelmin ( ENCOG_TRAIN_NM *nm, double start[], double xmin[] )
     {
       break;
     }
+
 /*
   Restart the procedure.
 */
@@ -411,16 +412,14 @@ ENCOG_TRAIN_NM *EncogTrainNMNew(ENCOG_NEURAL_NETWORK *network, ENCOG_DATA *data)
 	result->data = data;
 	result->targetNetwork = network;	
 	result->reportTarget = &EncogTrainStandardCallback;
-	result->error = 100;
+	result->error = 1.0;
 	result->network = network;
-	result->reqmin = 0.01;
-	result->konvge = 100;
+	result->step = EncogHashGetFloat(encogContext.config,PARAM_STEP,10.0);
+	result->reqmin = EncogHashGetFloat(encogContext.config,PARAM_REQMIN, 1.0e-16);
+	result->konvge = EncogHashGetInteger(encogContext.config,PARAM_KONVERGE,100);
 	result->ifault = 0;
 	memset(&result->currentReport,0,sizeof(ENCOG_TRAINING_REPORT));
 
-	EncogNetworkRandomizeRange(network,-1,1);
-
-
 	result->n = result->network->weightCount;
 	result->step = 1;
 
@@ -434,7 +433,6 @@ float EncogTrainNMRun(ENCOG_TRAIN_NM *nm)
 {
 	int n;
 	ENCOG_DATA *data;
-	double reqmin;
 	double *start;
 	double *xmin;
 
@@ -450,11 +448,8 @@ float EncogTrainNMRun(ENCOG_TRAIN_NM *nm)
 	data = nm->data;
 	n = nm->network->weightCount;
 	start = (double*)EncogUtilDuplicateMemory(nm->network->weights,n,sizeof(REAL));
-	reqmin = 0.001;
 	xmin = (double*)EncogUtilAlloc(n,sizeof(double));
 
-	nm->step = 1;
-
 	_nelmin ( nm, start, xmin );
 
 	nm->currentReport.error = nm->error;