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| courses:cs211:winter2012:journals:mike:home [2012/03/28 03:26] – [Memoization] whitem12 | courses:cs211:winter2012:journals:mike:home [2012/03/28 03:36] – [Least Squares] whitem12 | ||
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| If working backwards gets you the solution its probably going to be the way to go. | If working backwards gets you the solution its probably going to be the way to go. | ||
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| + | ==== Least Squares ==== | ||
| + | Finding the best fit line. Want to minimize the square of the deviations of data from a line. Data is given, find the line. There isn't always one line, sometimes multiple lines, but we want creating a new line to have a penalty, otherwise there would be a line from each data point to another datapoint and the SSE (sum of squares error) = 0. | ||
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| + | This can be made into a dynamic function by working backwards, you find the SSE for the last three points (otherwise it's 0 so it's easy) and then compair whether making a new partition is going to be more effective in minimizing the SSE + penalty or if it's more useful to just adjust the original line. | ||
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| + | This total adds up to O(n^2) | ||
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| + | ==== Adding a variable ==== | ||
