seq_gen3: RNN action sequence generator
In ProcData: Process Data Analysis

Description Usage Arguments Value See Also

seq_gen3 generates action sequences according to a recurrent neural network

seq_gen3(n, events = letters, rnn_type = "lstm", K = 10,
  weights = NULL, max_len = 100, initial_state = NULL,
  start_index = 1, end_index = length(events), include_time = FALSE,
  time_intv_dist = list("exp", 1))

`n`	An integer. The number of action sequences to be generated.
`events`	A character vector specifying the set of `N` possible actions. Default is `letters`.
`rnn_type`	the type of recurrent unit to be used for generating sequences. `"lstm"` for the long-short term memory unit. `"gru"` for the gated recurrent unit.
`K`	the latent dimension of the recurrent unit.
`weights`	a list containing the weights in the embedding layer, the recurrent unit, the fully connected layer. If not (properly) specified, randomly generated weights are used.
`max_len`	Maximum length of generated sequences.
`initial_state`	a list containing the initial state of the recurrent neural network. If `rnn_type="lstm"`, it contains two 1 by `K` matrices. If `rnn_type="gru"`, it contains one 1 by `K` matrix. If not specified, all the elements are set to zero.
`start_index`	Index of the action indicating the start of an item in `events`.
`end_index`	Index of the action indicating the end of an item in `events`.
`include_time`	logical. Indicate if timestamp sequences should be generated. Default is FALSE.
`time_intv_dist`	A list specifying the distribution of the inter-arrival time.