knn_regress

std.geometry.knn_regress · Level L3

k-nearest-neighbour regression: the mean value of the k points closest to q (ties by index). The ranks of the distances become a mask, so k can be an input.

(1/k)·Σ{ valuesᵢ : rank(‖Pᵢ − q‖²) < k }

Signature

knn_regress(q: f64[d], points: f64[m, d], values: f64[m], k: f64[]) → f64[]

Structure

The function as NOVA stores it: one box per input, operation and output, and arrows that carry values. A double border marks another library function this one runs — called once, or by Scan once per element; select it to open that function.

qf64[d]pointsf64[m, d]valuesf64[m]kf64[]SubtractdiffMultiplysqReduceSumdistrankrLessnearMultiplypickedReduceSumtotalDivideyyf64[]
  • input
  • operation
  • constant
  • call
  • output

Verification

  • Signature proven by NOVA’s shape solver, for every size.
  • Equal to the reference mean of values at np.argsort(dist2)[:k] in exact rational arithmetic, on all 40 test cases.
  • All 40 float64 results inside the running error bound; the closest uses 50% of it.
  • Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
correctly rounded (the float64 nearest the exact value)
90%
bit-equal to the NumPy formula in float64
93%
largest error, in units in the last place
1.50

Identity

Calls
rank
Called by
—
sha256:b252de30d878326b0632f690a58001683f69e499e91d128031b86d1167f585fa

The semantic hash of the graph. It changes when the program changes, and never when only its documentation does.