core/model.go


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// Model envelope persists trained model to JSON. Contains Vectorizer for IDF values,
// OrderedVocab for feature ordering, and Weights for logistic regression.
// To score: recreate TFIDFVectorizer, transform, then PredictScore.
package core

import (
	"time"
)

// ModelEnvelope - complete trained model for scoring articles
type ModelEnvelope struct {
	Algorithm    string             `json:"algorithm"`
	Impl         string             `json:"impl"`
	Version      string             `json:"version"`
	CreatedAt    time.Time          `json:"created_at"`
	Meta         map[string]any     `json:"meta"`
	Vectorizer   map[string]float64 `json:"vectorizer"`
	OrderedVocab []string           `json:"ordered_vocab"`
	Weights      []float64          `json:"weights"`
}