knn_regress
std.geometry.knn_regress · Level L3k-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.
- 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
sha256:b252de30d878326b0632f690a58001683f69e499e91d128031b86d1167f585faThe semantic hash of the graph. It changes when the program changes, and never when only its documentation does.
Control handle
- Symbol
- Ω:std.geometry.knn_regress · Ω:knn_regress
- Pins
sha256:0a9530654b3cc670c7f8a4615e68b36f899867b9434f27039688f4f61938e3c7this graph and the 1 it reaches through calls- Evidence
sha256:0f17b713f70fc6c8d97cd60922df336bf7b9e44e4bd67cb917c2974c3f1e9d3cthe hash of its verification record- Needs
- no capability: a pure function
Through NOVA’s control layer, the symbol launches this function only while the program still matches what it pins: a change to this graph, or to any graph it reaches, needs a migration first.