Re: BiasVariance Analysis
Thank you professor, I think I can work from here.

Re: BiasVariance Analysis
I am confused in trying to get from the first line to the second line for the first set of equations on page 63: ... ED[Ex[(g... on the first line to ...Ex[ED[( on the second line.
I sort of see the first line: expected value with respect to data set x (a subset of D I assume) is averaged over all possible data set x's in D. On the second line we have what might be the average of the argument over all of D inside the outer brackets. I don't know how to interpret Ex outside the outer brackets. In short, I certainly don't understand what exactly is meant by the 2nd line, and I may well not understand the first line. Any further explanation possible? 
Re: BiasVariance Analysis
Dear Prof. Yaser,
Can you explain more about variance, the simple idea and example of this? I read this paragraph but I still cannot fully understand. 'One can also view the variance as a measure of 'instability' in the learning model. Instability manifests in wild reactions to small variations or idiosyn* crasies in the data, resulting in vastly different hypotheses.' page 64 how does "small variations or idiosyn*crasies in the data" effect our final hypothesis (variance of linear model vs constant model for example)? Thank you very much! 
All times are GMT 7. The time now is 08:22 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. AbuMostafa, Malik MagdonIsmail, and HsuanTien Lin, and participants in the Learning From Data MOOC by Yaser S. AbuMostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.