MOESM1 of Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
1) Compiled Mtb activity datasets (TB_full_consolidate_Threshold X.sdf, 18,886 cmps) from many different experimental groups. These data were used as a training set for multiple Bayesian models. The a
The best set of parameters is {number of conv filters, Nc: 256, number of units in LSTM Nh: 64, dropout probability for Dropout Layer: 0, learning rate: 0.001} for read-level prediction on 5-fold cros
Intrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. Ho
