metric_concordance_index {DeepPINCS} | R Documentation |
The concordance index or c-index can be seen as one of the model performance metrics. It represents a good fit of the model.
Dongmin Jung
Kose, U., & Alzubi, J. (2020). Deep learning for cancer diagnosis. Springer.
keras::k_cast, keras::k_equal, keras::k_sum, tensorflow::tf
if (keras::is_keras_available() & reticulate::py_available()) { compound_length_seq <- 50 compound_embedding_dim <- 16 protein_embedding_dim <- 16 protein_length_seq <- 100 mlp_cnn_cpi <- fit_cpi( smiles = example_cpi[1:100, 1], AAseq = example_cpi[1:100, 2], outcome = example_cpi[1:100, 3], compound_type = "sequence", compound_length_seq = compound_length_seq, compound_embedding_dim = compound_embedding_dim, protein_length_seq = protein_length_seq, protein_embedding_dim = protein_embedding_dim, net_args = list( compound = "mlp_in_out", compound_args = list( fc_units = c(10), fc_activation = c("relu")), protein = "cnn_in_out", protein_args = list( cnn_filters = c(32), cnn_kernel_size = c(3), cnn_activation = c("relu"), fc_units = c(10), fc_activation = c("relu")), fc_units = c(1), fc_activation = c("sigmoid"), loss = "binary_crossentropy", optimizer = keras::optimizer_adam(), metrics = custom_metric("concordance_index", metric_concordance_index)), epochs = 2, batch_size = 16) }