/// <summary>
/// Query a regression algorithm using equilateral encoding.
/// </summary>
/// <param name="alg">The algorithm being used.</param>
/// <param name="theTrainingData">The training data.</param>
/// <param name="items">The category items classified.</param>
/// <param name="high">The high value.</param>
/// <param name="low">The low value.</param>
public static void QueryEquilateral(
IRegressionAlgorithm alg,
IList<BasicData> theTrainingData,
IDictionary<String, int> items,
double high, double low)
{
// first, we need to invert the items. Right now it maps from category to index. We need index to category.
IDictionary<int, String> invMap = new Dictionary<int, string>();
foreach (string key in items.Keys)
{
int value = items[key];
invMap[value] = key;
}
// now we can query
Equilateral eq = new Equilateral(items.Count, high, low);
foreach (BasicData data in theTrainingData)
{
double[] output = alg.ComputeRegression(data.Input);
int idealIndex = eq.Decode(data.Ideal);
int actualIndex = eq.Decode(output);
Console.WriteLine(VectorUtil.DoubleArrayToString(data.Input) + " -> " + invMap[actualIndex]
+ ", Ideal: " + invMap[idealIndex]);
}
}
public void TestDecode()
{
var eq = new Equilateral(3, -1, 1);
double[] d0 = { 0.866, 0.5 };
double[] d1 = { -0.866, 0.5 };
double[] d2 = { 0, -1 };
Assert.AreEqual(2, eq.Decode(d0));
Assert.AreEqual(2, eq.Decode(d1));
Assert.AreEqual(0, eq.Decode(d2));
}
