Prediction of Compound Profiling Matrices, Part II: Relative Performance of Multitask Deep Learning and Random Forest Classification on the Basis of Varying Amounts of Training Data

[Image: see text] Currently, there is a high level of interest in deep learning and multitask learning in many scientific fields including the life sciences and chemistry. Herein, we investigate the performance of multitask deep neural networks (MT-DNNs) compared to random forest (RF) classification...

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Detalles Bibliográficos
Autores principales: Rodríguez-Pérez, Raquel, Bajorath, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175492/
https://www.ncbi.nlm.nih.gov/pubmed/30320286
http://dx.doi.org/10.1021/acsomega.8b01682

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175492/
https://www.ncbi.nlm.nih.gov/pubmed/30320286
http://dx.doi.org/10.1021/acsomega.8b01682

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