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PREreview of Leveraging Quadratic Polynomials in Python for Advanced Data Analysis

CC BY 4.0

The manuscript is well-organized, with detailed and precise methods and implementation cases. The provided Python Notebook is especially handy. The proposed Python-formatted version of the code snippet for quadratic polynomials appears useful for researchers. Additionally, the code is available through However, I suggest that potential overfitting should be discussed to improve the manuscript's clarity and effectiveness. While a high R-squared value often suggests a good fit of the model to the data, it can also be misleading. A very high R-squared value can be a sign of overfitting, particularly in cases where the number of predictors (independent variables) is close to the number of observations.

Competing interests

The author declares that they have no competing interests.