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 (p _{c})]**

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(p _{c})** 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.

Version:

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 |

Example:

See NewNetTester_bn.