I posted this on sci.math and didn't get an answer, so I'll try here, where I probably should have asked in the first place.
Suppose you have two dictionaries D1,D2. Suppose that D1 is much smaller than D2, in the sense that it has fewer entries, but has a reputation for being more accurate than D2, in the sense that the probability of an entry of D2 being incorrect is much greater than that of an entry of D1 being incorrect. Suppose you want to know whether D2, whatever its faults, can usually be used for whatever one would want to use D1 for. One way to find out would be to go through D1, look up all the entries and compare them with the corresponding entries of D2 (when D2 has them). One can give credence to D1's reputation by assuming that when D1,D2 disagree, D1 is correct. However, if D1 has too many entries, this could be impractical. So, instead, I would like to know how to design an experiment in which one samples the entries of D1 and compares the entries in the same with their counterparts in D2, and arrives at an estimate for the probability that entries in D1 are correctly treated in D2. How does one design such a test and where can I read the details of how it is designed and evaluated? Ignorantly, Allan Adler [EMAIL PROTECTED] **************************************************************************** * * * Disclaimer: I am a guest and *not* a member of the MIT Artificial * * Intelligence Lab. My actions and comments do not reflect * * in any way on MIT. Moreover, I am nowhere near the Boston * * metropolitan area. * * * **************************************************************************** . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
