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Miha Kralj
2026-03-13 13:47:10 -07:00
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lib/numerics/normalize/Normalize.md
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| **PineScript** | [normalize.pine](normalize.pine) |
- The Normalize transformer applies min-max scaling to map any value series into the bounded range [0, 1] based on the observed minimum and maximum w...
- Parameterized by `period` (default 14).
- Output range: Varies (see docs).
- Requires `period` bars of warmup before first valid output (IsHot = true).
- **Trading note:** Min-max normalization to [0,1]; makes indicators comparable across different scales.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
The Normalize transformer applies min-max scaling to map any value series into the bounded range [0, 1] based on the observed minimum and maximum within a rolling lookback window. This technique is fundamental for feature scaling, creating bounded oscillators, and comparing series with different magnitudes.
@@ -231,4 +229,4 @@ Normalize.Calculate(prices, normalized, period: 20);
- Aksoy, S., & Haralick, R. M. (2001). "Feature normalization and likelihood-based similarity measures for image retrieval." *Pattern Recognition Letters*.
- Patro, S., & Sahu, K. K. (2015). "Normalization: A preprocessing stage." *IARJSET*.
- Géron, A. (2019). *Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow*. O'Reilly Media.
- Géron, A. (2019). *Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow*. O'Reilly Media.