public void F64Matrix_GetColumn()
{
// matrix is created row wise
var matrix = new F64Matrix(new double[] { 1, 2, 3,
4, 5, 6 }, 2, 3);
// returns the column as an array
var column = matrix.Column(1); // [2, 5]
}
/// <summary>
/// Creates a matrix of ordered indices. Each row is ordered after the corresponding feature column.
/// </summary>
/// <param name="observations"></param>
/// <param name="rows"></param>
/// <returns></returns>
int[][] CreateOrderedElements(F64Matrix observations, int rows)
{
var orderedElements = new int[observations.ColumnCount][];
for (int i = 0; i < observations.ColumnCount; i++)
{
var feature = observations.Column(i);
var indices = Enumerable.Range(0, rows).ToArray();
feature.SortWith(indices);
orderedElements[i] = indices;
}
return(orderedElements);
}
Dictionary <int, double> GetInitialRanking(F64Matrix crossValidatedModelPredictions, double[] targets)
{
var ranking = new Dictionary <int, double>();
var currentPredictions = new double[crossValidatedModelPredictions.RowCount];
for (int i = 0; i < crossValidatedModelPredictions.ColumnCount; i++)
{
crossValidatedModelPredictions.Column(i, currentPredictions);
var error = m_metric.Error(targets, currentPredictions);
ranking.Add(i, error);
}
return(ranking.OrderBy(v => v.Value).ToDictionary(v => v.Key, v => v.Value));
}