Some­how in the last few months I’d missed the seri­ous update of Michael Schmidt’s Eureqa pack­age for sym­bolic regres­sion. Now avail­able for Win­dows, Linux and Mac plat­forms, and fea­tur­ing a very nice cloud inte­gra­tion for addi­tional pro­cess­ing, this looks like a ground-breaker for usabil­ity and under­stand­abil­ity in Sym­bolic Regres­sion applications.

Here’s an intro­duc­tion video. Michael does a much bet­ter job explain­ing it suc­cinctly than I’ve seen before:

Inter­est­ingly, I stum­bled across Michael’s update because I was writ­ing to Cosma Shal­izi, fish­ing for feed­back from the Very Impor­tant Thinkers attend­ing the Ockham’s Razor Work­shop regard­ing (mod­ern, multi-objective) sym­bolic regres­sion of the style Michael’s project embod­ies. A lot of these same notions of Pareto Sym­bolic Regres­sion were devel­oped orig­i­nally by Mark Kotanchek, Katya Vladislavl­eva and Guido Smits from Dow Chem­i­cal and Evolved Ana­lyt­ics, recently released in Data­Mod­eler for Math­e­mat­ica.

It’s fas­ci­nat­ing to me how lit­tle pro­fes­sional atten­tion crosses in either direc­tion between the machine learning/statistical the­ory folks and genetic pro­gram­ming folks. Impor­tant work in both fields is essen­tially invis­i­ble across that divide. As the years go by the dichotomy is get­ting some­how deeper, to the point where I expect they’re just going to run into one another headed the other way, when they both cir­cum­nav­i­gate the net­work of All Pos­si­ble Approaches to Sci­ence and Engi­neer­ing in their rush apart….

Note, as clar­i­fi­ca­tion: I am not includ­ing any chap­ters on sym­bolic regres­sion in the book. Sym­bolic regres­sion is an amaz­ing and rapidly matur­ing field, and I count it pretty much “done” with the release of Data­Mod­eler and For­mulize. From here on, it’s a field in its own right, not least because the tricks and tech­niques use­ful in address­ing quan­ti­ta­tive mod­el­ing projects like these are quite dif­fer­ent from the qual­i­ta­tive and struc­tural mod­el­ing projects we’re doing in the book.

Still, down­load and play with Eure­qua II, and see what you can understand.