public void KNearestNeighborConstructorTest3()
{
// The k-Nearest Neighbors algorithm can be used with
// any kind of data. In this example, we will see how
// it can be used to compare, for example, Strings.
string[] inputs =
{
"Car", // class 0
"Bar", // class 0
"Jar", // class 0
"Charm", // class 1
"Chair" // class 1
};
int[] outputs =
{
0, 0, 0, // First three are from class 0
1, 1, // And next two are from class 1
};
// Now we will create the K-Nearest Neighbors algorithm. For this
// example, we will be choosing k = 1. This means that, for a given
// instance, only its nearest neighbor will be used to cast a new
// decision.
// In order to compare strings, we will be using Levenshtein's string distance
KNearestNeighbors<string> knn = new KNearestNeighbors<string>(k: 1, classes: 2,
inputs: inputs, outputs: outputs, distance: new Levenshtein());
// After the algorithm has been created, we can use it:
int answer = knn.Compute("Chars"); // answer should be 1.
Assert.AreEqual(1, answer);
}
