Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data

标题
Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
作者
关键词
Deep learning, SARs, Cheminformatics, Machine-learning, Data-mining, Random forest, kNN, Support vector machines, Naïve Bayes
出版物
Journal of Cheminformatics
Volume 9, Issue 1, Pages -
出版商
Springer Nature
发表日期
2017-06-28
DOI
10.1186/s13321-017-0226-y

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search