metric_concordance_index {DeepPINCS} | R Documentation

## Concordance index

### Description

The concordance index or c-index can be seen as one of the model performance metrics. It represents a good fit of the model.

### Author(s)

Dongmin Jung

### References

Kose, U., & Alzubi, J. (2020). Deep learning for cancer diagnosis. Springer.

### See Also

keras::k_cast, keras::k_equal, keras::k_sum, tensorflow::tf

### Examples

    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)
    }

[Package DeepPINCS version 1.2.2 Index]