Conditional probability estimator for a numeric domain conditional upon
a discrete domain (utilises separate normal estimators for each discrete
conditioning value).
Converts all numeric attributes into binary attributes (apart from
the class attribute): if the value of the numeric attribute is
exactly zero, the value of the new attribute will be zero.
Returns the value, x, for which the area under the
Normal (Gaussian) probability density function (integrated from
minus infinity to x) is equal to the argument y
(assumes mean is zero, variance is one).
Returns the area under the Normal (Gaussian) probability density
function, integrated from minus infinity to x
(assumes mean is zero, variance is one).