public void testOverlapPattern()
{
var classifier = new CLAClassifier <double>();
ClassificationExperiment <Double> result = compute(classifier, 0, new int[] { 1, 5 }, 9, 9);
result = compute(classifier, 1, new int[] { 1, 5 }, 9, 9);
result = compute(classifier, 1, new int[] { 1, 5 }, 9, 9);
result = compute(classifier, 2, new int[] { 3, 5 }, 2, 2);
// Since overlap - should be previous with 100%
checkValue(result, 9, 9.0, 1.0);
result = compute(classifier, 3, new int[] { 3, 5 }, 2, 2);
// Second example: now new value should be more probable than old
Assert.IsTrue(result.getStat(1, 2) > result.getStat(1, 9));
}
public void TestSingleValue()
{
var classifier = new CLAClassifier <double>(new List <int> {
0
}, 0.001, 0.3);
ClassificationExperiment <double> retVal = null;
for (int recordNum = 0; recordNum < 10; recordNum++)
{
retVal = compute(classifier, recordNum, new int[] { 1, 5 }, 0, 10);
}
Assert.AreEqual(10.0, retVal.getActualValue(0), .00001);
Assert.AreEqual(1.0, retVal.getStat(0, 0), .00001);
}
public void testComputeComplex()
{
var classifier = new CLAClassifier <double>(new List <int> {
1
}, 0.1, 0.1);
int recordNum = 0;
Dictionary <string, object> classification = new Dictionary <string, object>();
classification.Add("bucketIdx", 4);
classification.Add("actValue", 34.7);
ClassificationExperiment <double> result = classifier.Compute(recordNum, classification, new int[] { 1, 5, 9 }, true, true);
recordNum += 1;
classification["bucketIdx"] = 5;
classification["actValue"] = 41.7;
result = classifier.Compute(recordNum, classification, new int[] { 0, 6, 9, 11 }, true, true);
recordNum += 1;
classification["bucketIdx"] = 5;
classification["actValue"] = 44.9;
result = classifier.Compute(recordNum, classification, new int[] { 6, 9 }, true, true);
recordNum += 1;
classification["bucketIdx"] = 4;
classification["actValue"] = 42.9;
result = classifier.Compute(recordNum, classification, new int[] { 1, 5, 9 }, true, true);
recordNum += 1;
classification["bucketIdx"] = 4;
classification["actValue"] = 34.7;
result = classifier.Compute(recordNum, classification, new int[] { 1, 5, 9 }, true, true);
Assert.AreEqual(35.520000457763672, result.getActualValue(4), 0.00001);
Assert.AreEqual(42.020000457763672, result.getActualValue(5), 0.00001);
Assert.AreEqual(6, result.getStatCount(1));
Assert.AreEqual(0.0, result.getStat(1, 0), 0.00001);
Assert.AreEqual(0.0, result.getStat(1, 1), 0.00001);
Assert.AreEqual(0.0, result.getStat(1, 2), 0.00001);
Assert.AreEqual(0.0, result.getStat(1, 3), 0.00001);
Assert.AreEqual(0.12300123, result.getStat(1, 4), 0.00001);
Assert.AreEqual(0.87699877, result.getStat(1, 5), 0.00001);
}
/// <summary>
/// general method for checking expected probability and value
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="retVal">Result of compute method</param>
/// <param name="index">value of particular bucket index</param>
/// <param name="value">expected value</param>
/// <param name="probability">expected probability</param>
public void checkValue <T>(ClassificationExperiment <T> retVal, int index, Object value, double probability)
{
Assert.AreEqual(retVal.getActualValue(index), value);
Assert.AreEqual(probability, retVal.getStat(1, index), 0.01);
}