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Pre-Trained Models Multi-Output Random Forest Regression to Emulate the Earliest Stages of Planet Formation

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 05 Apr 2021Publisher:Zenodo
Authors: Zazzera, André; Hoffman, Kevin; Sung, Jae Yoon;

doi: 10.5281/zenodo.4662909 , 10.5281/zenodo.4662910

Pre-Trained Models Multi-Output Random Forest Regression to Emulate the Earliest Stages of Planet Formation

Abstract

These are pre-trained models made in Python, for use in the installation and running of the astrodust Python package. The files are for the random forest regressor, which can be used to predict dust coagulation in protoplanetary disks, and for a classifier, which predicts if the model's own predictions are trustworthy or potentially flawed.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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