/// <summary>
/// Normalizes features within the specified range (min, max)
/// </summary>
/// <param name="matrix"></param>
/// <param name="output"></param>
public void Transform(F64Matrix matrix, F64Matrix output)
{
var rows = matrix.RowCount;
var cols = matrix.ColumnCount;
if (m_featureMinMax.Count == 0)
{
for (int i = 0; i < cols; i++)
{
m_featureMinMax.Add(i, new FeatureMinMax {
Min = double.MaxValue, Max = double.MinValue
});
}
}
CreateFeatureMinMax(matrix);
for (int i = 0; i < cols; i++)
{
for (int j = 0; j < rows; j++)
{
var value = matrix[j, i];
var minMax = m_featureMinMax[i];
var newValue = m_normalizer.Normalize(m_min, m_max, minMax.Min, minMax.Max, value);
output[j, i] = newValue;
}
}
}
public void LinearNormalizer_Normalize()
{
var oldMin = -213.0;
var oldMax = 2345.0;
var newMin = -1.0;
var newMax = 1.0;
var sut = new LinearNormalizer();
Assert.AreEqual(1.0, sut.Normalize(newMin, newMax, oldMin, oldMax, oldMax), 0.000001);
Assert.AreEqual(-1.0, sut.Normalize(newMin, newMax, oldMin, oldMax, oldMin), 0.000001);
Assert.AreEqual(-0.833463643471462, sut.Normalize(newMin, newMax, oldMin, oldMax, 0.0), 0.000001);
Assert.AreEqual(0.730258014073495, sut.Normalize(newMin, newMax, oldMin, oldMax, 2000.0), 0.000001);
}
