| public GetPartitionSize ( int index, int &trainingCount, int &validationCount ) : void | ||
| index | int | The index of the bootstrap sample. |
| trainingCount | int | The number of instances in the training set. |
| validationCount | int | The number of instances in the validation set. |
| return | void | |
/// <summary>
/// Initializes a new instance of the <see cref="BootstrapResult"/> class.
/// </summary>
///
/// <param name="owner">The <see cref="Bootstrap"/> that is creating this result.</param>
/// <param name="models">The models created during the cross-validation runs.</param>
///
public BootstrapResult(Bootstrap owner, BootstrapValues[] models)
{
double[] trainingValues = new double[models.Length];
double[] trainingVariances = new double[models.Length];
int[] trainingCount = new int[models.Length];
double[] validationValues = new double[models.Length];
double[] validationVariances = new double[models.Length];
int[] validationCount = new int[models.Length];
for (int i = 0; i < models.Length; i++)
{
trainingValues[i] = models[i].TrainingValue;
trainingVariances[i] = models[i].TrainingVariance;
validationValues[i] = models[i].ValidationValue;
validationVariances[i] = models[i].ValidationVariance;
owner.GetPartitionSize(i, out trainingCount[i], out validationCount[i]);
}
this.Settings = owner;
this.Training = new CrossValidationStatistics(trainingCount, trainingValues, trainingVariances);
this.Validation = new CrossValidationStatistics(validationCount, validationValues, validationVariances);
this.Estimate = 0.632 * Validation.Mean + 0.368 * Training.Mean;
}
/// <summary>
/// Initializes a new instance of the <see cref="BootstrapResult"/> class.
/// </summary>
///
/// <param name="owner">The <see cref="Bootstrap"/> that is creating this result.</param>
/// <param name="models">The models created during the cross-validation runs.</param>
///
public BootstrapResult(Bootstrap owner, BootstrapValues[] models)
{
double[] trainingValues = new double[models.Length];
double[] trainingVariances = new double[models.Length];
int[] trainingCount = new int[models.Length];
double[] validationValues = new double[models.Length];
double[] validationVariances = new double[models.Length];
int[] validationCount = new int[models.Length];
for (int i = 0; i < models.Length; i++)
{
trainingValues[i] = models[i].TrainingValue;
trainingVariances[i] = models[i].TrainingVariance;
validationValues[i] = models[i].ValidationValue;
validationVariances[i] = models[i].ValidationVariance;
owner.GetPartitionSize(i, out trainingCount[i], out validationCount[i]);
}
this.Settings = owner;
this.Training = new CrossValidationStatistics(trainingCount, trainingValues, trainingVariances);
this.Validation = new CrossValidationStatistics(validationCount, validationValues, validationVariances);
this.Estimate = 0.632 * Validation.Mean + 0.368 * Training.Mean;
}
