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neural: Use optimizer adam
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1 changed files with 5 additions and 2 deletions
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@ -6,7 +6,7 @@
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# training data and validated using this set. For non-training genes, the
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# final score will be the mean of the result of applying the different
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# models.
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neural <- function(preset, progress = NULL, seed = 49641, n_models = 5) {
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neural <- function(preset, progress = NULL, seed = 751833, n_models = 5) {
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species_ids <- preset$species_ids
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gene_ids <- preset$gene_ids
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reference_gene_ids <- preset$reference_gene_ids
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@ -175,7 +175,10 @@ neural <- function(preset, progress = NULL, seed = 49641, n_models = 5) {
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units = 1,
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activation = "sigmoid"
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) |>
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keras::compile(loss = "binary_crossentropy")
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keras::compile(
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loss = keras::loss_binary_crossentropy(),
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optimizer = keras::optimizer_adam()
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)
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# Train the model.
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