public NearestNeighborsModel(LabelledData <T> trainingData, int numNeighbors, Func <double[], double[], double> distanceFunction)
{
int numRows = trainingData.Features.RowCount;
Points = new LabeledVector[numRows];
for (int i = 0; i < numRows; i++)
{
Points[i].features = trainingData.Features[i];
Points[i].label = trainingData.Labels[i];
}
K = numNeighbors;
DistanceFunction = distanceFunction;
}
/// <summary>
/// Test the error and accuracy of a set of labeled data.
/// </summary>
/// <param name="testData">The data to test the model against.</param>
/// <returns>The average prediction error and the percent accuracy.</returns>
public (double Error, double Accuracy) Test(LabelledData <T> testData)
{
return(Test(testData.Features, testData.Labels));
}
public LogisticRegressionModel(LabelledData <bool> trainingData, double learningRate, int numEpochs)
{
Train(trainingData.Features, trainingData.Labels.Select(l => l ? 1 : 0).ToArray(), learningRate, numEpochs);
}
