Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets

Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets

Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two limitations, high accuracy and abundance, are often...

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Bibliographic Details
Main Authors: Thomas M. Kaiser, Pieter B. Burger
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Molecules
Subjects:
machine learning
error
FEP
anaplastic lymphoma kinase (ALK)
Naïve Bayes Network
Random Forest
drug discovery
cheminformatics
Neural Network
Online Access:https://www.mdpi.com/1420-3049/24/11/2115

Internet

https://www.mdpi.com/1420-3049/24/11/2115

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