Difference between revisions of "Selection"
From Sean_Carver
(New page: First, the homework from Lab W. Today's topic is ''model selection.'' What is model selection? To answer this question let's contrast model selection with parameter ...) |
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First, the [[Media:Lab_W.pdf|homework from Lab W]]. | First, the [[Media:Lab_W.pdf|homework from Lab W]]. | ||
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| + | == What is Model Selection? == | ||
Today's topic is ''model selection.'' What is model selection? To answer this question let's contrast model selection with parameter estimation. Recall that the Optimization Lab fit lines to data. For the Optimization lab we were doing parameter estimation, trying to estimate the parameters m,b, in the formula for a line y = m*x + b. Recall the examples from the Optimization Lab: we fit a line to nearly linear data and another line to nearly parabolic data. | Today's topic is ''model selection.'' What is model selection? To answer this question let's contrast model selection with parameter estimation. Recall that the Optimization Lab fit lines to data. For the Optimization lab we were doing parameter estimation, trying to estimate the parameters m,b, in the formula for a line y = m*x + b. Recall the examples from the Optimization Lab: we fit a line to nearly linear data and another line to nearly parabolic data. | ||
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| + | [[Image:DataBestLine.jpg|center|thumb|300px|Fitting a line to nearly linear data. Click for full size image]] | ||
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| + | In this case, a line fits well. In the following example a parabola fits better than a line, but we can still ask, what's the best line? The best line is shown: | ||
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| + | [[Image:DataBestParab.jpg|center|thumb|300px|Fitting a line to nearly parabolic data. Click for full size image]] | ||
Revision as of 15:19, 22 April 2009
First, the homework from Lab W.
What is Model Selection?
Today's topic is model selection. What is model selection? To answer this question let's contrast model selection with parameter estimation. Recall that the Optimization Lab fit lines to data. For the Optimization lab we were doing parameter estimation, trying to estimate the parameters m,b, in the formula for a line y = m*x + b. Recall the examples from the Optimization Lab: we fit a line to nearly linear data and another line to nearly parabolic data.
In this case, a line fits well. In the following example a parabola fits better than a line, but we can still ask, what's the best line? The best line is shown:
