/* TRAINING EXAMPLES METHODS */
/// <summary>
/// Adds a training example based on the configuration in the editor
/// </summary>
public void AddTrainingExample()
{
RapidlibTrainingExample newExample = new RapidlibTrainingExample();
// Calculate size of the new example input vector [I CAN MOVE THIS TO THE START OF THE PROGRAM]
int sizeNewExampleInput = 0;
for (int i = 0; i < m_Features.Count; i++)
{
sizeNewExampleInput += (m_LengthsFeatureVector[i] * inputs.Length);
}
newExample.Input = new double[sizeNewExampleInput];
m_ExtractFeatures(ref newExample.Input, inputs);
newExample.Output = new double[outputs.Length];
for (int i = 0; i < outputs.Length; i++)
{
newExample.Output[i] = outputs[i];
}
m_EasyRapidlib.AddTrainingExample(newExample);
}
/// <summary>
/// Adds an already created training example to rapidlib
/// </summary>
/// <param name="newExample"></param>
public void AddTrainingExample(RapidlibTrainingExample newExample)
{
m_EasyRapidlib.AddTrainingExample(newExample);
}
