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Module Owl_nlp_tfidf

module Owl_nlp_tfidf: sig .. end
NLP: TFIDF module
module Vec: Owl_dense_vector_d
type tf_typ =
| Binary
| Count
| Frequency
| Log_norm 
type df_typ =
| Unary
| Idf
| Idf_Smooth 
type t = {
   mutable uri : string;
   mutable tf_typ : tf_typ;
   mutable df_typ : df_typ;
   mutable offset : int array;
   mutable doc_freq : float array;
   mutable corpus : Owl_nlp_corpus.t;
   mutable handle : Pervasives.in_channel option;
} 
val term_freq : tf_typ -> float -> float -> float
val doc_freq : df_typ -> float -> float -> float
val tf_typ_string : tf_typ -> string
val df_typ_string : df_typ -> string
val create : tf_typ ->
       df_typ -> Owl_nlp_corpus.t -> t
val get_uri : t -> string
val get_corpus : t -> Owl_nlp_corpus.t
val length : t -> int
val vocab_len : t -> int
val get_handle : t -> Pervasives.in_channel
val doc_count_of : t -> string -> float
val doc_count : Owl_nlp_vocabulary.t -> string -> float array * int
val term_count : ('a, float) Hashtbl.t -> 'a array -> unit
val normalise : ('a * float) array -> ('a * float) array
val _build_with : bool ->
       bool ->
       (float -> float -> float) ->
       (float -> float -> float) -> t -> unit
val build : ?norm:bool ->
       ?sort:bool ->
       ?tf:tf_typ ->
       ?df:df_typ -> Owl_nlp_corpus.t -> t
val next : t -> (int * float) array
val next_batch : ?size:int -> t -> (int * float) array array
val iteri : (int -> 'a -> 'b) -> t -> unit
val mapi : (int -> 'a -> 'b) -> t -> 'b array
val get : t -> int -> (int * float) array
val reset_iterators : t -> unit
val apply : t -> string -> (int * float) array
val save : t -> string -> unit
val load : string -> t
val to_string : t -> string
val print : t -> unit
val density : t -> float
val doc_to_vec : t -> (int * Vec.elt) array -> Vec.vec
val all_pairwise_distance : Owl_nlp_similarity.t ->
       t -> ('a * float) array -> (int * float) array
val nearest : ?typ:Owl_nlp_similarity.t ->
       t -> ('a * float) array -> int -> (int * float) array