| public Write ( String str ) : void | ||
| str | String | The string to write. |
| Résultat | void | |
/// <inheritdoc/>
public void Save(Stream os, Object obj)
{
EncogWriteHelper o = new EncogWriteHelper(os);
BayesianNetwork b = (BayesianNetwork)obj;
o.AddSection("BAYES-NETWORK");
o.AddSubSection("BAYES-PARAM");
String queryType = "";
String queryStr = b.ClassificationStructure;
if (b.Query != null)
{
queryType = b.Query.GetType().Name;
}
o.WriteProperty("queryType", queryType);
o.WriteProperty("query", queryStr);
o.WriteProperty("contents", b.Contents);
o.AddSubSection("BAYES-PROPERTIES");
o.AddProperties(b.Properties);
o.AddSubSection("BAYES-TABLE");
foreach (BayesianEvent e in b.Events)
{
foreach (TableLine line in e.Table.Lines)
{
if (line == null)
continue;
StringBuilder str = new StringBuilder();
str.Append("P(");
str.Append(BayesianEvent.FormatEventName(e, line.Result));
if (e.Parents.Count > 0)
{
str.Append("|");
}
int index = 0;
bool first = true;
foreach (BayesianEvent parentEvent in e.Parents)
{
if (!first)
{
str.Append(",");
}
first = false;
int arg = line.Arguments[index++];
if (parentEvent.IsBoolean)
{
if (arg == 0)
{
str.Append("+");
}
else
{
str.Append("-");
}
}
str.Append(parentEvent.Label);
if (!parentEvent.IsBoolean)
{
str.Append("=");
if (arg >= parentEvent.Choices.Count)
{
throw new BayesianError("Argument value " + arg + " is out of range for event " + parentEvent.ToString());
}
str.Append(parentEvent.GetChoice(arg));
}
}
str.Append(")=");
str.Append(line.Probability);
str.Append("\n");
o.Write(str.ToString());
}
}
o.Flush();
}
/// <inheritdoc/>
public void Save(Stream os, Object obj)
{
var xout = new EncogWriteHelper(os);
var svm2 = (SupportVectorMachine) obj;
xout.AddSection("SVM");
xout.AddSubSection("PARAMS");
xout.AddProperties(svm2.Properties);
xout.AddSubSection("SVM-PARAM");
xout.WriteProperty(PersistConst.InputCount, svm2.InputCount);
xout.WriteProperty(ParamC, svm2.Params.C);
xout.WriteProperty(ParamCacheSize,
svm2.Params.cache_size);
xout.WriteProperty(ParamCoef0, svm2.Params.coef0);
xout.WriteProperty(ParamDegree, svm2.Params.degree);
xout.WriteProperty(ParamEps, svm2.Params.eps);
xout.WriteProperty(ParamGamma, svm2.Params.gamma);
xout.WriteProperty(ParamKernelType,
svm2.Params.kernel_type);
xout.WriteProperty(ParamNumWeight,
svm2.Params.nr_weight);
xout.WriteProperty(ParamNu, svm2.Params.nu);
xout.WriteProperty(ParamP, svm2.Params.p);
xout.WriteProperty(ParamProbability,
svm2.Params.probability);
xout.WriteProperty(ParamShrinking,
svm2.Params.shrinking);
/* xout.WriteProperty(PersistSVM.PARAM_START_ITERATIONS,
svm2.Params.statIterations); */
xout.WriteProperty(ParamSVMType, svm2.Params.svm_type);
xout.WriteProperty(ParamWeight, svm2.Params.weight);
xout.WriteProperty(ParamWeightLabel,
svm2.Params.weight_label);
if (svm2.Model != null)
{
xout.AddSubSection("SVM-MODEL");
try
{
var ba = new MemoryStream();
var w = new StreamWriter(ba);
svm.svm_save_model(w, svm2.Model);
var enc = new ASCIIEncoding();
xout.Write(enc.GetString(ba.ToArray()));
w.Close();
ba.Close();
}
catch (IOException ex)
{
throw new PersistError(ex);
}
}
xout.Flush();
}
public void Save(Stream os, object obj)
{
SupportVectorMachine machine;
EncogWriteHelper helper = new EncogWriteHelper(os);
if (8 != 0)
{
}
Label_026A:
machine = (SupportVectorMachine) obj;
helper.AddSection("SVM");
if (0 == 0)
{
while (true)
{
helper.AddSubSection("PARAMS");
helper.AddProperties(machine.Properties);
helper.AddSubSection("SVM-PARAM");
helper.WriteProperty("inputCount", machine.InputCount);
helper.WriteProperty("C", machine.Params.C);
if (0 == 0)
{
helper.WriteProperty("cacheSize", machine.Params.cache_size);
if (-2 == 0)
{
goto Label_026A;
}
helper.WriteProperty("coef0", machine.Params.coef0);
helper.WriteProperty("degree", machine.Params.degree);
helper.WriteProperty("eps", machine.Params.eps);
helper.WriteProperty("gamma", machine.Params.gamma);
helper.WriteProperty("kernelType", machine.Params.kernel_type);
}
helper.WriteProperty("nrWeight", machine.Params.nr_weight);
if (1 != 0)
{
helper.WriteProperty("nu", machine.Params.nu);
helper.WriteProperty("p", machine.Params.p);
helper.WriteProperty("probability", machine.Params.probability);
helper.WriteProperty("shrinking", machine.Params.shrinking);
helper.WriteProperty("svmType", machine.Params.svm_type);
helper.WriteProperty("weight", machine.Params.weight);
helper.WriteProperty("weightLabel", machine.Params.weight_label);
break;
}
}
}
Label_0092:
while (machine.Model != null)
{
helper.AddSubSection("SVM-MODEL");
try
{
StreamWriter writer;
ASCIIEncoding encoding;
MemoryStream stream = new MemoryStream();
if (1 != 0)
{
goto Label_005F;
}
Label_003E:
helper.Write(encoding.GetString(stream.ToArray()));
writer.Close();
stream.Close();
break;
Label_005F:
writer = new StreamWriter(stream);
if (0 == 0)
{
svm.svm_save_model(writer, machine.Model);
}
encoding = new ASCIIEncoding();
goto Label_003E;
}
catch (IOException exception)
{
throw new PersistError(exception);
}
}
while (true)
{
helper.Flush();
if (-2147483648 != 0)
{
return;
}
if (0 != 0)
{
goto Label_0092;
}
}
}
