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Modeling Variance: A Variance-Motivated Approach to Molecular Prediction

revised on 19.11.2020, 13:43 and posted on 20.11.2020, 04:51 by na'il mitchell
In this variance-motivated study, the variance of a multi-thousand molecular dataset of Coulomb matrices is analyzed. This paper presents novel statistical methods and models that can aide in molecular prediction and analysis. A blended statistical/ML model is introduced for classifying data as Normal as well as a model for visualizing variance. Linear regression is also used to show a potential simple and 1 dimensional molecular descriptor, for some molecules. Paper includes literature review.


Email Address of Submitting Author


Chemathon Inc



ORCID For Submitting Author


Declaration of Conflict of Interest

no conflict of interest

Version Notes

Paper was updated to list additional information for regression results. Typo in figure of classification tree was corrected.