The technique behind Ufinq
Symbolic Regression.
Finding the formula in the data.
Symbolic Regression searches the space of mathematical expressions for one that explains your data. Not the parameters of a fixed-form model, but the formula itself: shape, operations, constants, all discovered.
Most modeling picks a shape first and tunes it to fit. Symbolic Regression does the opposite: it lets the shape itself compete. Thousands of candidate formulas rise and fall until the one that truly explains the data survives.
Ufinq is Diafunc's Symbolic Regression technology, and it goes far beyond evolutionary search. These are only foundations; there is much more.
x1 x1 · x2 sin(x1) + x2 0.42 · sin(2π · x1) + 1.8 · x22 − 0.31
Generations of competing programs. One wins.
- · Every candidate is tuned and simplified before it competes
- · Decompositional learning splits hard problems apart and recomposes them
- · The search runs at scale, across generations of competing programs
- · One model comes back, automatically as simple as the data allows
- · The research, papers, and benchmarks live at ufinq.com
Diafunc's Symbolic Regression technology (research, papers, benchmarks) is at ufinq.com.
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