learn_class_box — Train the classifier.
learn_class_box is obsolete and is only provided for reasons of backward compatibility. New applications should use the MLP, SVM, KNN or GMM operators instead.
Features is a tuple of any floating point numbers or integers (attributes) which has to be assigned to the class Class. This class is specified by an integer. You may use the operator enquire_class_box later to find the most probable class for any array (=tupel). The algorithm tries to describe the set of arrays of one class by hyper cuboids in the feature space. On demand you may even create several cuboids per class. Hence it is possible to learn disjunct concepts, too. I.e such concepts which split in several “cluster” of points in the feature space. The data structure is hidden to the user and only accessible with such operators which are described in this chapter.
Note that if a class consists of disjunct sub-classes that would lead to a splitting of the respective hyper cuboid, the training samples should be in random order with respect to the sub-classes. Otherwise, the splitting of the hyper cuboid will be sub-optimal.
It is possible to specify attributes as unknown by indicating the symbol '*' instead of a number. If you specify n values, then all following values, i.e. the attributes n+1 until 'max', are automatically supposed to be undefined.
You may call the operators learn_class_box and enquire_class_box alternately, so that it is possible to classify already in the phase of learning. By this means you could see when a satisfying behavior had been reached.
The classifier is going to be bigger using further training. This means, that it is not advisable to continue training after reaching a satisfactory behavior.
This operator modifies the state of the following input parameter:
Handle of the classifier.
Array of attributes to learn.
Default value: [1.0,1.5,2.0]
Class to which the array has to be assigned.
Default value: 1
learn_class_box returns 2 (H_MSG_TRUE) for a normal case. An exception is raised if there are memory allocation problems. The number of classes is constrained. If this limit is passed, an exception is raised, too.
test_sampset_box, enquire_class_box, write_class_box, close_class_box, clear_sampset
test_sampset_box, close_class_box, create_class_box, enquire_class_box, learn_sampset_box