(image_size, subject_names)
return ExtendedPredictableModel(feature=feature, classifier=classifier, image_size=image_size, subject_names=subject_names)
This method returns the PredictableModel which is used to learn a model
        for possible further usage. If you want to define your own model, this
        is the method to return it from!
This method returns the PredictableModel which is used to learn a model
        for possible further usage. If you want to define your own model, this
        is the method to return it from!
This method returns the PredictableModel which is used to learn a model for possible further usage . If you want to define your own model this is the method to return it from!
def get_model(image_size, subject_names):
    """ This method returns the PredictableModel which is used to learn a model
        for possible further usage. If you want to define your own model, this
        is the method to return it from!
    """
    # Define the Fisherfaces Method as Feature Extraction method:
    feature = Fisherfaces()
    # Define a 1-NN classifier with Euclidean Distance:
    classifier = NearestNeighbor(dist_metric=EuclideanDistance(), k=1)
    # Return the model as the combination:
    return ExtendedPredictableModel(feature=feature, classifier=classifier, image_size=image_size, subject_names=subject_names)
def get_model ( image_size , subject_names ) : # Define the Fisherfaces Method as Feature Extraction method: feature = Fisherfaces ( ) # Define a 1-NN classifier with Euclidean Distance: classifier = NearestNeighbor ( dist_metric = EuclideanDistance ( ) , k = 1 ) # Return the model as the combination: return ExtendedPredictableModel ( feature = feature , classifier = classifier , image_size = image_size , subject_names = subject_names )