A finite inverse minimum
Penguin learning project
The project uses 342 complete Palmer penguin records: 240 training-pool and 102 held-out rows. The selected training rows determine feature scaling and model parameters. Source CSV
This project trains weights with softmax, unlike the homepage lab, which uses nearest species averages. Same penguin measurements; different classification methods. Predictions can differ.
Inverse problems · Describe reconstruction from observations using a forward operator.
This application has its own inputs and assumptions; the penguin measurements are not its experimental data.
Consider this concept alongside the project; its source assumptions may differ. These observations do not prove a theorem.
Input: 12 × 2; Held-out evaluation: 102 · #58 · 40.6 mm, 193 mm. Known answer: Adélie; Prediction: Adélie · [≈0.7383, ≈0.2444, ≈0.01737].
Used in these source sections: 8.1 Working back from measurements
Choose the network parameter that minimizes squared mismatch after applying the forward operator.
This example shows the source’s optimization-based inverse reconstruction.
Source formula example
exact · This chosen linear model has a closed-form solution; other inverse problems may not.
Symbols
- Forward map; toy K(y) = 2y.
- Parameter-dependent candidate; toy Φ(ξ,θ) = ξθ.
- Fixed input, here 1.
- Real parameter.
- Observation.
Source formula example
This source example uses its own inputs and assumptions. Editing it does not change the project.
Edit a value or the code, then run the example. This is a finite demonstration, not a proof of the paper’s theorem.
This example’s data flow
Code changed. Reset to restore this example’s data flow.
You choose
input.observed= 3
Initial values in code
xi=1
Calculated here
Result expression: { theta, candidate, residual, minimum: residual ** 2 }
observed=input.observedUses:input.observedtheta=observed / 2Uses:observedcandidate=xi * thetaUses:xi,thetaresidual=2 * candidate - observedUses:candidate,observed
Returns
theta- 1.5
candidate- 1.5
residual- 0
minimum- 0
Read numbers from input and return the result. JavaScript basics.
Result
Technical statement
Here the parameter domain is all real numbers, so θ = x/2 is the exact minimizer and the minimum is zero.
Source: Source expression