![]() |
#1
|
|||
|
|||
![]()
Should the out-of-sample data set also be 100 randomly-generated points or should it be larger like in several of the earlier homeworks? Thanks for your attention.
|
#2
|
||||
|
||||
![]() Quote:
![]()
__________________
Where everyone thinks alike, no one thinks very much |
#3
|
|||
|
|||
![]() |
#4
|
|||
|
|||
![]()
In general the answers alternatives have good margins. If you run at least 1000 experiments, you should get "reasonable results" (E_out) on average with at least 100 test points. As always in machine learning, the more test data, the better.
|
#5
|
|||
|
|||
![]()
I settled in 200 points for testing, the same set for all batch of 1000 runs, and Eout seemed very stable.
|
#6
|
|||
|
|||
![]() For questions 17 and 18, my answers are different from one set of experiments to the next. Can't say any more, but I'm wondering if anyone else had a similar experience. Thanks. -Samir |
![]() |
Thread Tools | |
Display Modes | |
|
|