Table 8 Table summarizes the accuracy of ANN, GRU, BILSTM, LSTM, and 1DCNN model for 107 SNPs
From: Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods
Model, SNPs = 107 | Activation | Dropout | Optimizer | Batchsize | Epochs | Validation | Accuracy |
|---|---|---|---|---|---|---|---|
ANN | Sigmoid | 0.3 | SGD | 1 | 50 | 0.3 | 0.9 |
Relu | 0.2 | SGD | 1 | 10 | 0.3 | 0.9 | |
Softmax | 0.2 | Adam | 1 | 10 | 0.2 | 0.91 | |
Relu | 0.3 | SGD | 15 | 50 | 0.2 | 0.91 | |
LSTM | Relu | 0.2 | SGD | 10 | 50 | 0.2 | 0.9 |
Relu | 0.3 | Adam | 1 | 20 | 0.2 | 0.9 | |
Relu | 0.3 | SGD | 1 | 50 | 0.2 | 0.9 | |
Sigmoid | 0.2 | SGD | 1 | 10 | 0.4 | 0.91 | |
1DCNN | Sigmoid | 0.2 | Adam | 1 | 20 | 0.3 | 0.92 |
Sigmoid | 0.2 | Adam | 1 | 50 | 0.3 | 0.91 | |
Relu | 0.3 | Adam | 1 | 20 | 0.2 | 0.895 |