package owl

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NLP: LDA module

module MD = Owl_dense.Matrix.D
type lda_typ =
  1. | SimpleLDA
  2. | FTreeLDA
  3. | LightLDA
  4. | SparseLDA
type dsmat = (float, Stdlib.Bigarray.float64_elt) Owl_dense_matrix_generic.t
type spmat = (float, Stdlib.Bigarray.float64_elt) Owl_sparse_dok_matrix.t
type model = {
  1. mutable n_d : int;
  2. mutable n_k : int;
  3. mutable n_v : int;
  4. mutable alpha : float;
  5. mutable beta : float;
  6. mutable alpha_k : float;
  7. mutable beta_v : float;
  8. mutable t_dk : dsmat;
  9. mutable t_wk : spmat;
  10. mutable t__k : dsmat;
  11. mutable t__z : int array array;
  12. mutable iter : int;
  13. mutable data : int array array;
  14. mutable vocb : (string, int) Stdlib.Hashtbl.t;
}
val include_token : model -> int -> int -> int -> unit
val exclude_token : model -> int -> int -> int -> unit
val likelihood : model -> float
val show_info : model -> int -> float -> unit
module SimpleLDA : sig ... end
module SparseLDA : sig ... end
module FTreeLDA : sig ... end
module LightLDA : sig ... end
val init : ?iter:int -> int -> (string, int) Stdlib.Hashtbl.t -> int array array -> model
val train : lda_typ -> model -> unit
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