- **Chapter 2 - Training versus Testing**
(*http://book.caltech.edu/bookforum/forumdisplay.php?f=109*)

- - **equation 2.13 on page 57**
(*http://book.caltech.edu/bookforum/showthread.php?t=4702*)

equation 2.13 on page 57I've been reading the book in parallel with watching the lectures. I think that equation 2.13 on page 57 is wrong or perhaps just misleading. The expression right before equation 2.13 is of the form
N >= const * ln(m(2N)) for fixed eps and delta. Then equation 2.10, m(N) <= 1+N^d_vc, is used to rewrite the expression as equation 2.13, N >= const * ln(1+(2N)^d_vc) But all we can really say from these two expressions is N >= const * ln(m(2N)) <= const * ln(1+(2N)^d_vc) In other words, I don't see how I can know the sign of the inequality "?" in N ? const * ln(1+(2N)^d_vc) What am I missing:clueless: This seems an important thing, so please help me see my error.... |

All times are GMT -7. The time now is 05:29 PM. |

Powered by vBulletin® Version 3.8.3

Copyright ©2000 - 2019, Jelsoft Enterprises Ltd.

The contents of this forum are to be used ONLY by readers of the Learning From Data book by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin, and participants in the Learning From Data MOOC by Yaser S. Abu-Mostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.