learn_classif2 ( : : Features, Class : )

Training of the current classificator.

Features is a tupel 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 procedure enquire_classif2 later on to get 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 create even 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 accessible with the aid of in this chapter explained procedures only.

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 supposed to be undefined automatically.

You may call the procedures learn_classif2 and enquire_classif2 alternately, so that it is possible to classificate already in the phase of learning. By this means you may indicate if a satisfying behavior had been reached.

The classificator is going to be bigger using further training. This means, that it is not advisable to continue training after reaching a satisfactory behavior.


Parameters

Features (input_control)
number-array -> real / integer / string
Array of attributes to learn.
Default value: '[1.0,1.5,2.0]'

Class (input_control)
integer -> integer
Class, to which the array has to be assigned.
Default value: 1


Result

learn_classif2 returns TRUE in a normal case. An exception handling is raised, if there is no current classificator (see set_classif2), or if there are memory allocation problems. The number of classes is constrained (ca. 50). If this limit is passed, an exception handling is raised, too.


Possible Predecessors

create_classif2, enquire_classif2, set_classif2


Possible Successors

test_sampset2, learn_classif2, enquire_classif2, write_classif2, close_classif2, free_sampset


See also

test_sampset2, close_classif2, create_classif2, enquire_classif2, get_classif2, learn_sampset2, set_classif2



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