Machine Learning Model Building Floes Release Notes

v0.12.1 February 2025

• This package is built using OpenEye-orionplatform==6.2.0, OpenEye-toolkits==2024.2.0, OpenEye-Snowball==0.28.1, and OpenEye-floereport==6.2.0.

Feature Updates

• There is now a baseline XGBoost model with every ML Build floe. The performance of these XGBoost models is reported in the Floe Report and output success model.

• Several bug fixes have been made.

New Floe in this package

ML Predict: XGBoost for Small Molecules Floe

The XGBoost models built by default using ML Build floes can be used as input here. This floe can be used to predict the properties of small molecules using XGBoost from the ML Build floes. It will act as a classifier if the base model is a classifier trained on String and will act as a regressor if trained on Float. The floe autoselects the type of prediction based on the provided model. If the model was trained on a custom feature vector, please provide a field in the input molecule dataset containing the feature vector; otherwise, the floe will fail.