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RNN Model Class

Source: R/Model_RNNModel.R
RNN.Rd

A full‑featured classification model that (i) embeds each input feature with EmbeddingModel, (ii) processes each feature sequence through its own RNNLayer, and (iii) concatenates the final hidden states for prediction.

Usage

RNN(dataset = NULL, embedding_dim = 128, hidden_dim = 128, ...)

Arguments

dataset

A SampleDataset object providing input/output schema.

embedding_dim

Integer, embedding width for each token. Default 128.

hidden_dim

Integer, hidden size of each RNN. Default 128.

...

Additional arguments forwarded to each RNNLayer (except input_size/hidden_size, which are fixed by embedding_dim / hidden_dim).

Details

  • Works for binary, multi‑class, or regression labels (inferred from dataset).

  • Supports optional mask per feature (all‑zero rows are treated as padding).

  • All internal indices comply with R's 1‑based rule; no device mismatches.