For some reason, Aleks doesn't blog anymore; he just sends me things to blog. I guess he's decided his time is more usefully spent doing other things. I, however, continue to enjoy blogging as an alternative to real work and am a sucker for all the links Aleks sends me (except for the videos, which I never watch).
Aleks's latest find is a program called Eureqa that implements a high-tech curve-fitting method of Michael Schmidt and Hod Lipson. (And, unlike Clarence Thomas, I mean "high-tech" in a good way.) Schmidt and Lipson describe their algorithm as "distilling free-form natural laws from experimental data," which seems a bit over the top, but the basic idea seems sound: Instead of simply running a linear regression, the program searches through a larger space of functional forms, building models like Tinker Toys by continually adding components until the fit stops improving:
I have some thoughts on the limitations of this approach (see below), but to get things started I wanted to try out an example where I suspected this new approach would work well where more traditional statistical methods would fail.
The example I chose was a homework assignment that I included in a couple of my books. Here's the description:
I give students the following twenty data points and ask them to fit y as a function of x1 and x2.y x1 x2
15.68 6.87 14.09
6.18 4.4 4.35
18.1 0.43 18.09
9.07 2.73 8.65
17.97 3.25 17.68
10.04 5.3 8.53
20.74 7.08 19.5
9.76 9.73 0.72
8.23 4.51 6.88
6.52 6.4 1.26
15.69 5.72 14.62
15.51 6.28 14.18
20.61 6.14 19.68
19.58 8.26 17.75
9.72 9.41 2.44
16.36 2.88 16.1
18.3 5.74 17.37
13.26 0.45 13.25
12.1 3.74 11.51
18.15 5.03 17.44
16.8 9.67 13.74
16.55 3.62 16.15
18.79 2.54 18.62
15.68 9.15 12.74
4.08 0.69 4.02
15.45 7.97 13.24
13.44 2.49 13.21
20.86 9.81 18.41
16.05 7.56 14.16
6 0.98 5.92
3.29 0.65 3.22
9.41 9 2.74
10.76 7.83 7.39
5.98 0.26 5.97
19.23 3.64 18.89
15.67 9.28 12.63
7.04 5.66 4.18
21.63 9.71 19.32
17.84 9.36 15.19
7.49 0.88 7.43[If you want to play along, try to fit the data before going on.]
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