Thread: Q4) h(x) = ax View Single Post
#9
02-01-2013, 12:19 PM
 yaser Caltech Join Date: Aug 2009 Location: Pasadena, California, USA Posts: 1,478
Re: Q4) h(x) = ax

Quote:
 Originally Posted by Anne Paulson So, in this procedure we: Pick two points; Find the best slope for those two points, the one that minimizes the squared error for those two points; Do this N times and average all the s Rather than: Pick two points; Calculate the squared error for those two points as a function of ; Do this N times, then find the that minimizes the sum of all of the squared errors, as we do with linear regression Are we doing the first thing here or the second thing? Either way there's a simple analytic solution, but I'm not sure which procedure we're doing.
The first method estimates for the average hypothesis (which takes into consideration only two points at a time). The second method estimates for the best approximation of the target function (which takes into consideration all the points in the input space at once).
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