6. The learning apparatus as claimed in claim 2 , wherein the threshold value learning unit learns the abort threshold value on the basis of the result of addition of the product of the result of estimation of the weak hypothesis with respect to negative data labeled as the non-detection target, of the data set, and the reliability of the weak hypothesis, calculated and added every time a weak hypothesis is selected by the weak hypothesis selection unit.
6. The learning apparatus as claimed in claim 2 , wherein the threshold value learning unit learns the abort threshold value on the basis of the result of addition of the product of the result of estimation of the weak hypothesis with respect to negative data labeled as the non-detection target, of the data set, and the reliability of the weak hypothesis, calculated and added every time a weak hypothesis is selected by the weak hypothesis selection unit. 7. The learning apparatus as claimed in claim 6 , wherein the threshold value learning unit stores a larger one of a maximum value of the result of calculation with respect to the negative data and a discrimination boundary value, as the abort threshold value, every time the weak hypothesis is selected.