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

- - **Questions on Probability**
(*http://book.caltech.edu/bookforum/showthread.php?t=407*)

Questions on ProbabilityI have a question on the use of the Expectation Value operation as used in the class and the book.
My (simplistic) understanding of the expectation value of a quantity is basically like taking a weighted average: for random variable X with probability distribution Pr(X) the expectation value would be either a sum (if X is discrete) or an integral (X is continuous) over all X values of X_i * Pr(X=X_i). And then I would multiply everything by a 1/N or a 1/Delta(X). Is this more or less what is meant in the class by the E[] notation? Maybe I just need to become more comfortable using this operation, however language like that on page 61 of the book where the in sample error is defined as an averaging procedure in (implied?) contrast to the definition of E_out leaves me confused. Isn't expectation a weighted average *by definition*? Thanks for your help! |

All times are GMT -7. The time now is 03:41 PM. |

Powered by vBulletin® Version 3.8.3

Copyright ©2000 - 2021, 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.