LFD Book Forum Conflicting Lessons?
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#1
08-04-2012, 11:43 AM
 samirbajaj Member Join Date: Jul 2012 Location: Silicon Valley Posts: 48
Conflicting Lessons?

Dear Professor:

(I have asked stupid questions before, but I have no shame, so in that spirit, here's another one )

1) Lecture 8 - slide 16 - "Lesson Learned" - Match model complexity to data resources

2) Lecture 9 - slide 8 - "Lesson Learned" - Looking at data before choosing your model can be hazardous

-Samir
#2
08-06-2012, 09:31 PM
 Mayson Lancaster Junior Member Join Date: Jul 2012 Posts: 7
Re: Conflicting Lessons?

Actually, it seems that the two do not quite conflict.

The first lesson: match model complexity to data resources, means that you vary the complexity of your model based on how much data you have [perhaps employing a heuristic such as N = 10*dvc or dvc = N/10]

The second says that you should not look at the data itself, not merely the amount of data, but the fine structure, distribution, features, etc.

(I'd be glad to get feedback from course staff as to how well my attempted explanation gets at the meaning of the two sayings.)
#3
08-06-2012, 10:43 PM
 yaser Caltech Join Date: Aug 2009 Location: Pasadena, California, USA Posts: 1,478
Re: Conflicting Lessons?

Quote:
 Originally Posted by Mayson Lancaster Actually, it seems that the two do not quite conflict. The first lesson: match model complexity to data resources, means that you vary the complexity of your model based on how much data you have [perhaps employing a heuristic such as N = 10*dvc or dvc = N/10] The second says that you should not look at the data itself, not merely the amount of data, but the fine structure, distribution, features, etc. (I'd be glad to get feedback from course staff as to how well my attempted explanation gets at the meaning of the two sayings.)
The feedback from the course staff is positive.
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#4
08-07-2012, 12:02 PM
 gah44 Invited Guest Join Date: Jul 2012 Location: Seattle, WA Posts: 153
Re: Conflicting Lessons?

I presume in this case "look" means a computer looked at the data.

Probably worse if a person looks at the data. People are very good at finding patterns, even if there isn't one, and, even worse, remembering patterns from previous (unrelated) data sets and applying them.

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