func Train(ctx context.Context, pool *pgxpool.Pool, modelKey string, l2 float64, minEvents int, dryRun bool) (TrainResult, error) · (calibrated

Read the equation

This relation defines (calibrated in the source section “func Train(ctx context.Context, pool *pgxpool.Pool, modelKey string, l2 float64, minEvents int, dryRun bool) (TrainResult, error) · (calibrated”. It specifies the displayed relationship between the named quantities or parameters. Its interpretation depends on the source’s stated variables and conditions; this record does not assign an unprovided physical or cognitive meaning to them.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

1. Read (calibrated as the quantity being defined or updated by this relation.

2. Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.

3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

• This source expression was recovered from the pinned code revision. Its presence does not establish that the associated program was built, run, or scientifically validated.

Original context

	res.Version = version
	return res, nil
}

// materializeCalibration fits Platt scaling on the in sample log odds and materializes it into monotone
// calibration bins over the raw probability range [0, 1], the shape aedt_calibration_bins stores and the serve
// path looks up. For each bin the empirical rate is the Platt calibrated probability at the bin midpoint
// (calibrated = sigmoid(a * logit(mid) + b)). A Platt fit failure returns no bins, the honest identity map.
func materializeCalibration(etas []float64, y []int, binCount int) []Bin {
	a, b, err := learn.FitPlatt(etas, y)
	if err != nil {
		return nil
	}
	bins := make([]Bin, 0, binCount)
	for k := 0; k < binCount; k++ {
		lo := float64(k) / float64(binCount)
		hi := float64(k+1) / float64(binCount)
		mid := (lo + hi) / 2

(calibrated = sigmoid(a * logit(mid) + b)). A Platt fit failure returns no bins, the honest identity map.

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