Lodestar.Metrics 0.3.0. This page is frozen at that release. Read the current documentation for what main says now. A link to a decision or a migration page follows main, and leaves the archive.

The same four counts as a 2×2 array, in scikit-learn's own order.

public long[,] ToArray()

Parameters — none.

Returns — long[,], always [[DifferentInBoth, SameInPredictedOnly], [SameInTrueOnly, SameInBoth]] — the same shape pair_confusion_matrix returns in numpy.

Example — reading a computed matrix both ways.

using Lodestar.Metrics;

PairConfusionMatrix pairs = PairConfusionMatrix.Compute([0, 0, 1, 1], [1, 1, 0, 0]);
long[,] grid = pairs.ToArray();
long topLeft = grid[0, 0];   // => 8
long bottomRight = grid[1, 1];   // => 4

Remarks — for reading ported Python side by side, where the code indexes C[0, 1] or C[1, 0] and you want the same indices to mean the same thing. Writing new code, prefer the named properties on PairConfusionMatrix instead: [0,1] and [1,0] are easy to transpose by accident, and SameInPredictedOnly cannot be mistaken for SameInTrueOnly the way two array indices can.

The matrix is not symmetric — scikit-learn's own documentation says so — and this array does not fix that: grid[0, 1] and grid[1, 0] answer different questions, exactly as SameInPredictedOnly and SameInTrueOnly do.

Applies to — net10.0, netstandard2.0.

See also — PairConfusionMatrix, PairConfusionMatrix.Compute.