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.


Versions 2.08 and later have this function.

See also:

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


See NewNetTester_bn.