|NORSYS SOFTWARE © 2012||NETICA API||C   VERSION   5.04 |
|double GetTestLogLoss_bn (||tester_bn* test, node_bn* node )|
Returns the "logarithmic loss" of node under the tests previously performed with test.
The "logarithmic loss" is defined as: MOAC [ - log (pc)]
where MOAC stands for the mean (average) over all cases (i.e., all cases
for which the case file provides a value for the node in question), and
where log(pc) is the natural logarithm of the probability predicted for the state that turns out to be correct.
Values for logarithmic loss vary from 0 to infinity (inclusive), with 0 being a perfect score. If you must use a single number to grade the predictive/diagnostic quality of a net with respect to a certain discrete node, then we recommend the logarithmic loss.
node is required to have been in the test_nodes list originally passed to NewNetTester_bn.
|GetTestConfusion_bn||Get elements of the confusion matrix|
|GetTestErrorRate_bn||Get the fraction of test cases for which the prediction failed|
|GetTestQuadraticLoss_bn||Get the "quadratic loss" score of the test|
|NewNetTester_bn||Construct the tester_bn object|
|GetMutualInfo_bn||Find the mutual info (entropy reduction) between two nodes|