Exact(8)
The models obtained can be employed to predict activities of the compounds designed and/or form predictions for compounds that exist and have not yet been examined with biological inhibitory assays.
Commonly, the employed features are then used with machine learning approaches like support-vector-machines or decision trees to predict activities for previously unseen compounds.
They are treated implicitly and translated into other formats such as matrices so that machine learning techniques such as support vector machines (SVM) [21] can be used to predict activities or properties.
The decision tree was subsequently used to predict activities of the NCI60 test dataset.
It is important to determine how useful mean antimicrobial activities of species in different orders are to predict activities of other species in that order.
Next, we developed fuzzy Boolean network model to predict activities of nodes as functions of combinatorial stimulation of the EGF, IGF, and insulin receptors.
Similar(52)
Three machine learning methods were used to predict activity labels.
Unfortunately, most QSAR models predict activity against only one protein.
Results showed that the MLR predict activity in a satisfactory manner for both activities.
Results showed that the MLR and MNLR predict activity in a satisfactory manner.
The ability to predict activity coefficients at infinite dilution is discussed.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com