/* 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); }