ml_paramscan Stable-plateau parameter selection
The overfit cure: when you scan a parameter, don’t pick the single BEST-scoring value (that cell is almost always overfit) — pick the robust PLATEAU that scores well AND consistently. Score each variant by mean − λ·std and choose the argmax. Turns any parametric script self-tuning and overfit-resistant.
Design: the host runs the variants in parallel (a small state array per candidate parameter) and keeps each variant’s running performance mean and std; this library scores and selects. Pure functions of the arrays you pass; nothing repaints.
Concept credit: stability-over-optimum (plateau) parameter selection is a standard walk-forward / robustness practice — original, dependency-free Pine v6 packaging. Educational; not financial advice.
Library "ml_paramscan"
plateauScore(mean, std, lambda)
Parameters:
mean (float)
std (float)
lambda (simple float)
stablePlateau(means, stds, lambda)
Parameters:
means (array<float>)
stds (array<float>)
lambda (simple float)
bestPlateauScore(means, stds, lambda)
Parameters:
means (array<float>)
stds (array<float>)
lambda (simple float)
Design: the host runs the variants in parallel (a small state array per candidate parameter) and keeps each variant’s running performance mean and std; this library scores and selects. Pure functions of the arrays you pass; nothing repaints.
Concept credit: stability-over-optimum (plateau) parameter selection is a standard walk-forward / robustness practice — original, dependency-free Pine v6 packaging. Educational; not financial advice.
Library "ml_paramscan"
plateauScore(mean, std, lambda)
Parameters:
mean (float)
std (float)
lambda (simple float)
stablePlateau(means, stds, lambda)
Parameters:
means (array<float>)
stds (array<float>)
lambda (simple float)
bestPlateauScore(means, stds, lambda)
Parameters:
means (array<float>)
stds (array<float>)
lambda (simple float)
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這些資訊和出版物並非旨在提供，也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。