Extracts information on the selected (Q)SAR model from a Flare™ project. The Flare project can be either the output of one of the 'Flare Build' nodes or read in by the 'Flare Project Reader' node.
This node wraps the 'pyflare' executable, which must be installed with a valid license for this node to work. If this is installed in the default location on Windows, then it should be found automatically. Otherwise, you must either set the 'Cresset Home' preference setting or the CRESSET_HOME environment variable to the base Cresset software install directory. You may also set the 'pyflare Path' preference or the CRESSET_PYFLARE_EXE environment variable to point directly at the executable itself.
For more information visit www.cresset-group.com or contact us at support@cresset-group.com.
Options
Basic
Input Ports
- A Flare project with a (Q)SAR model. The 'Flare Build' nodes, Flare or the ‘pyflare’ executable with the ‘qsarbuild.py’ python script can be used to create the Flare project.
Output Ports
- The log of the model including the settings used to create the model.
- Statistics on the generated model including the r^2/q^2 and the recommended number of components/neighbors to use when scoring molecules with the model. Field QSAR and kNN Machine Learning models may have missing values for some of the columns whenever these metrics are not applicable. Activity Atlas and other types of Machine Learning models do not have any statistics so the table will be empty.
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