private Attribute BuildAttributeOfTypeImpl(EAttributeType atttype, PropertyInfo prop, string name)
{
Attribute att;
if (atttype == EAttributeType.Nominal)
{
att = GetNominalAttribute(prop);
}
else if (atttype == EAttributeType.Numeric)
{
att = new Attribute(name);
}
else if (atttype == EAttributeType.Binary)
{
att = new Attribute(name, binary);
}
else if (atttype == EAttributeType.String)
{
att = new Attribute(name, (ArrayList)null);
}
else if (atttype == EAttributeType.Date)
{
att = new Attribute(name, ISO_8601_DATE_FORMAT); // ISO-8601 Format
}
else
{
throw new NotSupportedException(atttype + " is not a supported attribute atttype.");
}
return(att);
}
public void test_attribute_to_enumerable_gives_nothing_on_numerics()
{
Runtime rt = TestingHelpers.LoadSmallRuntime <TitanicDataRow2>("titanic_train.csv", 0, 10);
weka.core.Attribute age = rt.Impl.attribute(4);
System.Collections.Generic.IEnumerable <string> values = age.ToEnumerable();
Assert.AreEqual(new string[0], values);
}
public void test_attribute_to_enumerable_gives_all_distinct_nominal_vals()
{
Runtime rt = TestingHelpers.LoadSmallRuntime <TitanicDataRow>("titanic_train.csv", 0, 10);
weka.core.Attribute pcclass = rt.Impl.attribute(1);
System.Collections.Generic.IEnumerable <string> values = pcclass.ToEnumerable();
Assert.AreEqual(new[] { "1", "2", "3" }, values);
}
public void TestCreationOfEnums()
{
// Arrange
var values = new weka.core.FastVector();
values.addElement("beech");
values.addElement("oak");
values.addElement("ash");
var attribute = new weka.core.Attribute("trees", values);
var repo = new EnumRepository();
// Act
var enumValue = repo.GetEnumValue(attribute, 0);
// Assert
var fields = enumValue.GetType().GetFields();
Assert.AreEqual(3, fields.Length);
Assert.AreEqual("beech", fields[0].Name);
}
/// <summary>
/// Uses the classifier to classify an instance (from its featureValues).
/// </summary>
/// <param name="featureValues">An array of doubles that describe the instance.</param>
/// <returns>The string name of the classification of the instance.</returns>
public string classify(double[] featureValues)
{
//if (!classifierBuilt) { _classifier.buildClassifier(_dataSet); classifierBuilt = true; }
weka.core.Instance inst = new weka.core.Instance(1, featureValues);
inst.setDataset(_dataSet);
double result = _classifier.classifyInstance(inst);
weka.core.Attribute attribute = _dataSet.attribute(_dataSet.numAttributes() - 1);
string resultName = attribute.value((int)result);
// Get rid of this line once ARFF files are rewritten
if (resultName == "Label")
{
resultName = "Text";
}
//Console.WriteLine(resultName);
return(resultName);
}
public int InitializeClassifier(string[] atributes, string[] gestures, string classAttribute, string modelLocation)
{
java.io.ObjectInputStream ois = new java.io.ObjectInputStream(new java.io.FileInputStream(modelLocation));
m_cl = (weka.classifiers.Classifier)ois.readObject();
//Declare the feature vector
weka.core.FastVector fvWekaFeatureVector = new weka.core.FastVector(atributes.Length + 1);
for (int i = 0; i < atributes.Length; i++)
{
weka.core.Attribute aux = new weka.core.Attribute(atributes[i]);
fvWekaFeatureVector.addElement(aux);
}
//Declare the class weka.core.Attribute along with its values
weka.core.FastVector fvClassValues = new weka.core.FastVector(gestures.Length);
for (int i = 0; i < gestures.Length; i++)
{
weka.core.Attribute z1 = new weka.core.Attribute(atributes[i]);
fvClassValues.addElement(gestures[i]);
}
//fvClassValues.addElement("yes");
//fvClassValues.addElement("no");
weka.core.Attribute ClassAttribute = new weka.core.Attribute(classAttribute, fvClassValues);
fvWekaFeatureVector.addElement(ClassAttribute);
dataSet = new weka.core.Instances("TestRel", fvWekaFeatureVector, 10);
dataSet.setClassIndex(atributes.Length);
testInstance = new weka.core.Instance(atributes.Length + 1);
return(1);
}
