- **Chapter 1 - The Learning Problem**
(*http://book.caltech.edu/bookforum/forumdisplay.php?f=108*)

- - **Equation 1.3**
(*http://book.caltech.edu/bookforum/showthread.php?t=4662*)

Equation 1.3I understand from the equation 1.3 that on every iteration we are improving the line that will act as a classifier. This line is defined by the weights and we are improving the weights. So we take the last known weights W(t) and add y(t)X(t) to it to get the new and better weights W(t+1)
What I don't understand is how did we compute that the increase in W(t) to get W(t+1) should be y(t)X(t) ? Thanks |

All times are GMT -7. The time now is 08:39 PM. |

Powered by vBulletin® Version 3.8.3

Copyright ©2000 - 2020, 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.