Source file Naive_bayes.ml

let () = Wrap_utils.init ();;
let __wrap_namespace = Py.import "sklearn.naive_bayes"

let get_py name = Py.Module.get __wrap_namespace name
module BaseDiscreteNB = struct
type tag = [`BaseDiscreteNB]
type t = [`BaseDiscreteNB | `BaseEstimator | `ClassifierMixin | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module BaseNB = struct
type tag = [`BaseNB]
type t = [`BaseEstimator | `BaseNB | `ClassifierMixin | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module BernoulliNB = struct
type tag = [`BernoulliNB]
type t = [`BaseEstimator | `BernoulliNB | `ClassifierMixin | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
                  let create ?alpha ?binarize ?fit_prior ?class_prior () =
                     Py.Module.get_function_with_keywords __wrap_namespace "BernoulliNB"
                       [||]
                       (Wrap_utils.keyword_args [("alpha", Wrap_utils.Option.map alpha Py.Float.of_float); ("binarize", Wrap_utils.Option.map binarize (function
| `F x -> Py.Float.of_float x
| `None -> Py.none
)); ("fit_prior", Wrap_utils.Option.map fit_prior Py.Bool.of_bool); ("class_prior", Wrap_utils.Option.map class_prior (function
| `Arr x -> Np.Obj.to_pyobject x
| `Size_ x -> Wrap_utils.id x
))])
                       |> of_pyobject
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject

let class_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_count_" with
  | None -> failwith "attribute class_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_count_ self = match class_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_log_prior_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_log_prior_" with
  | None -> failwith "attribute class_log_prior_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_log_prior_ self = match class_log_prior_opt self with
  | None -> raise Not_found
  | Some x -> x

let classes_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "classes_" with
  | None -> failwith "attribute classes_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let classes_ self = match classes_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_count_" with
  | None -> failwith "attribute feature_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_count_ self = match feature_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_log_prob_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_log_prob_" with
  | None -> failwith "attribute feature_log_prob_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_log_prob_ self = match feature_log_prob_opt self with
  | None -> raise Not_found
  | Some x -> x

let n_features_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "n_features_" with
  | None -> failwith "attribute n_features_ not found"
  | Some x -> if Py.is_none x then None else Some (Py.Int.to_int x)

let n_features_ self = match n_features_opt self with
  | None -> raise Not_found
  | Some x -> x
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module CategoricalNB = struct
type tag = [`CategoricalNB]
type t = [`BaseEstimator | `CategoricalNB | `ClassifierMixin | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
                  let create ?alpha ?fit_prior ?class_prior () =
                     Py.Module.get_function_with_keywords __wrap_namespace "CategoricalNB"
                       [||]
                       (Wrap_utils.keyword_args [("alpha", Wrap_utils.Option.map alpha Py.Float.of_float); ("fit_prior", Wrap_utils.Option.map fit_prior Py.Bool.of_bool); ("class_prior", Wrap_utils.Option.map class_prior (function
| `Size x -> Wrap_utils.id x
| `Arr x -> Np.Obj.to_pyobject x
))])
                       |> of_pyobject
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject

let category_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "category_count_" with
  | None -> failwith "attribute category_count_ not found"
  | Some x -> if Py.is_none x then None else Some (Wrap_utils.id x)

let category_count_ self = match category_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_count_" with
  | None -> failwith "attribute class_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_count_ self = match class_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_log_prior_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_log_prior_" with
  | None -> failwith "attribute class_log_prior_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_log_prior_ self = match class_log_prior_opt self with
  | None -> raise Not_found
  | Some x -> x

let classes_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "classes_" with
  | None -> failwith "attribute classes_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let classes_ self = match classes_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_log_prob_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_log_prob_" with
  | None -> failwith "attribute feature_log_prob_ not found"
  | Some x -> if Py.is_none x then None else Some (Wrap_utils.id x)

let feature_log_prob_ self = match feature_log_prob_opt self with
  | None -> raise Not_found
  | Some x -> x

let n_features_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "n_features_" with
  | None -> failwith "attribute n_features_ not found"
  | Some x -> if Py.is_none x then None else Some (Py.Int.to_int x)

let n_features_ self = match n_features_opt self with
  | None -> raise Not_found
  | Some x -> x
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module ComplementNB = struct
type tag = [`ComplementNB]
type t = [`BaseEstimator | `ClassifierMixin | `ComplementNB | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
                  let create ?alpha ?fit_prior ?class_prior ?norm () =
                     Py.Module.get_function_with_keywords __wrap_namespace "ComplementNB"
                       [||]
                       (Wrap_utils.keyword_args [("alpha", Wrap_utils.Option.map alpha Py.Float.of_float); ("fit_prior", Wrap_utils.Option.map fit_prior Py.Bool.of_bool); ("class_prior", Wrap_utils.Option.map class_prior (function
| `Size x -> Wrap_utils.id x
| `Arr x -> Np.Obj.to_pyobject x
)); ("norm", Wrap_utils.Option.map norm Py.Bool.of_bool)])
                       |> of_pyobject
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject

let class_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_count_" with
  | None -> failwith "attribute class_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_count_ self = match class_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_log_prior_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_log_prior_" with
  | None -> failwith "attribute class_log_prior_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_log_prior_ self = match class_log_prior_opt self with
  | None -> raise Not_found
  | Some x -> x

let classes_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "classes_" with
  | None -> failwith "attribute classes_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let classes_ self = match classes_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_all_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_all_" with
  | None -> failwith "attribute feature_all_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_all_ self = match feature_all_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_count_" with
  | None -> failwith "attribute feature_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_count_ self = match feature_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_log_prob_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_log_prob_" with
  | None -> failwith "attribute feature_log_prob_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_log_prob_ self = match feature_log_prob_opt self with
  | None -> raise Not_found
  | Some x -> x

let n_features_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "n_features_" with
  | None -> failwith "attribute n_features_ not found"
  | Some x -> if Py.is_none x then None else Some (Py.Int.to_int x)

let n_features_ self = match n_features_opt self with
  | None -> raise Not_found
  | Some x -> x
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module GaussianNB = struct
type tag = [`GaussianNB]
type t = [`BaseEstimator | `ClassifierMixin | `GaussianNB | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
let create ?priors ?var_smoothing () =
   Py.Module.get_function_with_keywords __wrap_namespace "GaussianNB"
     [||]
     (Wrap_utils.keyword_args [("priors", Wrap_utils.Option.map priors Np.Obj.to_pyobject); ("var_smoothing", Wrap_utils.Option.map var_smoothing Py.Float.of_float)])
     |> of_pyobject
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject

let class_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_count_" with
  | None -> failwith "attribute class_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_count_ self = match class_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_prior_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_prior_" with
  | None -> failwith "attribute class_prior_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_prior_ self = match class_prior_opt self with
  | None -> raise Not_found
  | Some x -> x

let classes_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "classes_" with
  | None -> failwith "attribute classes_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let classes_ self = match classes_opt self with
  | None -> raise Not_found
  | Some x -> x

let epsilon_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "epsilon_" with
  | None -> failwith "attribute epsilon_ not found"
  | Some x -> if Py.is_none x then None else Some (Py.Float.to_float x)

let epsilon_ self = match epsilon_opt self with
  | None -> raise Not_found
  | Some x -> x

let sigma_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "sigma_" with
  | None -> failwith "attribute sigma_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let sigma_ self = match sigma_opt self with
  | None -> raise Not_found
  | Some x -> x

let theta_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "theta_" with
  | None -> failwith "attribute theta_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let theta_ self = match theta_opt self with
  | None -> raise Not_found
  | Some x -> x
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
module MultinomialNB = struct
type tag = [`MultinomialNB]
type t = [`BaseEstimator | `ClassifierMixin | `MultinomialNB | `Object] Obj.t
let of_pyobject x = ((Obj.of_pyobject x) : t)
let to_pyobject x = Obj.to_pyobject x
let as_classifier x = (x :> [`ClassifierMixin] Obj.t)
let as_estimator x = (x :> [`BaseEstimator] Obj.t)
                  let create ?alpha ?fit_prior ?class_prior () =
                     Py.Module.get_function_with_keywords __wrap_namespace "MultinomialNB"
                       [||]
                       (Wrap_utils.keyword_args [("alpha", Wrap_utils.Option.map alpha Py.Float.of_float); ("fit_prior", Wrap_utils.Option.map fit_prior Py.Bool.of_bool); ("class_prior", Wrap_utils.Option.map class_prior (function
| `Size x -> Wrap_utils.id x
| `Arr x -> Np.Obj.to_pyobject x
))])
                       |> of_pyobject
let fit ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "fit"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let get_params ?deep self =
   Py.Module.get_function_with_keywords (to_pyobject self) "get_params"
     [||]
     (Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
     |> Dict.of_pyobject
let partial_fit ?classes ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "partial_fit"
     [||]
     (Wrap_utils.keyword_args [("classes", Wrap_utils.Option.map classes Np.Obj.to_pyobject); ("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> of_pyobject
let predict ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_log_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_log_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let predict_proba ~x self =
   Py.Module.get_function_with_keywords (to_pyobject self) "predict_proba"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let score ?sample_weight ~x ~y self =
   Py.Module.get_function_with_keywords (to_pyobject self) "score"
     [||]
     (Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> Py.Float.to_float
let set_params ?params self =
   Py.Module.get_function_with_keywords (to_pyobject self) "set_params"
     [||]
     (match params with None -> [] | Some x -> x)
     |> of_pyobject

let class_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_count_" with
  | None -> failwith "attribute class_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_count_ self = match class_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let class_log_prior_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "class_log_prior_" with
  | None -> failwith "attribute class_log_prior_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let class_log_prior_ self = match class_log_prior_opt self with
  | None -> raise Not_found
  | Some x -> x

let classes_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "classes_" with
  | None -> failwith "attribute classes_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let classes_ self = match classes_opt self with
  | None -> raise Not_found
  | Some x -> x

let coef_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "coef_" with
  | None -> failwith "attribute coef_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let coef_ self = match coef_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_count_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_count_" with
  | None -> failwith "attribute feature_count_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_count_ self = match feature_count_opt self with
  | None -> raise Not_found
  | Some x -> x

let feature_log_prob_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "feature_log_prob_" with
  | None -> failwith "attribute feature_log_prob_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let feature_log_prob_ self = match feature_log_prob_opt self with
  | None -> raise Not_found
  | Some x -> x

let intercept_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "intercept_" with
  | None -> failwith "attribute intercept_ not found"
  | Some x -> if Py.is_none x then None else Some ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) x)

let intercept_ self = match intercept_opt self with
  | None -> raise Not_found
  | Some x -> x

let n_features_opt self =
  match Py.Object.get_attr_string (to_pyobject self) "n_features_" with
  | None -> failwith "attribute n_features_ not found"
  | Some x -> if Py.is_none x then None else Some (Py.Int.to_int x)

let n_features_ self = match n_features_opt self with
  | None -> raise Not_found
  | Some x -> x
let to_string self = Py.Object.to_string (to_pyobject self)
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)

end
let abstractmethod funcobj =
   Py.Module.get_function_with_keywords __wrap_namespace "abstractmethod"
     [||]
     (Wrap_utils.keyword_args [("funcobj", Some(funcobj ))])

let binarize ?threshold ?copy ~x () =
   Py.Module.get_function_with_keywords __wrap_namespace "binarize"
     [||]
     (Wrap_utils.keyword_args [("threshold", Wrap_utils.Option.map threshold Py.Float.of_float); ("copy", Wrap_utils.Option.map copy Py.Bool.of_bool); ("X", Some(x |> Np.Obj.to_pyobject))])

                  let check_X_y ?accept_sparse ?accept_large_sparse ?dtype ?order ?copy ?force_all_finite ?ensure_2d ?allow_nd ?multi_output ?ensure_min_samples ?ensure_min_features ?y_numeric ?warn_on_dtype ?estimator ~x ~y () =
                     Py.Module.get_function_with_keywords __wrap_namespace "check_X_y"
                       [||]
                       (Wrap_utils.keyword_args [("accept_sparse", Wrap_utils.Option.map accept_sparse (function
| `StringList x -> (Py.List.of_list_map Py.String.of_string) x
| `S x -> Py.String.of_string x
| `Bool x -> Py.Bool.of_bool x
)); ("accept_large_sparse", Wrap_utils.Option.map accept_large_sparse Py.Bool.of_bool); ("dtype", Wrap_utils.Option.map dtype (function
| `S x -> Py.String.of_string x
| `Dtype x -> Np.Dtype.to_pyobject x
| `Dtypes x -> (fun ml -> Py.List.of_list_map Np.Dtype.to_pyobject ml) x
| `None -> Py.none
)); ("order", Wrap_utils.Option.map order (function
| `F -> Py.String.of_string "F"
| `C -> Py.String.of_string "C"
)); ("copy", Wrap_utils.Option.map copy Py.Bool.of_bool); ("force_all_finite", Wrap_utils.Option.map force_all_finite (function
| `Allow_nan -> Py.String.of_string "allow-nan"
| `Bool x -> Py.Bool.of_bool x
)); ("ensure_2d", Wrap_utils.Option.map ensure_2d Py.Bool.of_bool); ("allow_nd", Wrap_utils.Option.map allow_nd Py.Bool.of_bool); ("multi_output", Wrap_utils.Option.map multi_output Py.Bool.of_bool); ("ensure_min_samples", Wrap_utils.Option.map ensure_min_samples Py.Int.of_int); ("ensure_min_features", Wrap_utils.Option.map ensure_min_features Py.Int.of_int); ("y_numeric", Wrap_utils.Option.map y_numeric Py.Bool.of_bool); ("warn_on_dtype", Wrap_utils.Option.map warn_on_dtype Py.Bool.of_bool); ("estimator", Wrap_utils.Option.map estimator Np.Obj.to_pyobject); ("X", Some(x |> Np.Obj.to_pyobject)); ("y", Some(y |> Np.Obj.to_pyobject))])
                       |> (fun x -> ((Wrap_utils.id (Py.Tuple.get x 0)), (Wrap_utils.id (Py.Tuple.get x 1))))
                  let check_array ?accept_sparse ?accept_large_sparse ?dtype ?order ?copy ?force_all_finite ?ensure_2d ?allow_nd ?ensure_min_samples ?ensure_min_features ?warn_on_dtype ?estimator ~array () =
                     Py.Module.get_function_with_keywords __wrap_namespace "check_array"
                       [||]
                       (Wrap_utils.keyword_args [("accept_sparse", Wrap_utils.Option.map accept_sparse (function
| `StringList x -> (Py.List.of_list_map Py.String.of_string) x
| `S x -> Py.String.of_string x
| `Bool x -> Py.Bool.of_bool x
)); ("accept_large_sparse", Wrap_utils.Option.map accept_large_sparse Py.Bool.of_bool); ("dtype", Wrap_utils.Option.map dtype (function
| `S x -> Py.String.of_string x
| `Dtype x -> Np.Dtype.to_pyobject x
| `Dtypes x -> (fun ml -> Py.List.of_list_map Np.Dtype.to_pyobject ml) x
| `None -> Py.none
)); ("order", Wrap_utils.Option.map order (function
| `F -> Py.String.of_string "F"
| `C -> Py.String.of_string "C"
)); ("copy", Wrap_utils.Option.map copy Py.Bool.of_bool); ("force_all_finite", Wrap_utils.Option.map force_all_finite (function
| `Allow_nan -> Py.String.of_string "allow-nan"
| `Bool x -> Py.Bool.of_bool x
)); ("ensure_2d", Wrap_utils.Option.map ensure_2d Py.Bool.of_bool); ("allow_nd", Wrap_utils.Option.map allow_nd Py.Bool.of_bool); ("ensure_min_samples", Wrap_utils.Option.map ensure_min_samples Py.Int.of_int); ("ensure_min_features", Wrap_utils.Option.map ensure_min_features Py.Int.of_int); ("warn_on_dtype", Wrap_utils.Option.map warn_on_dtype Py.Bool.of_bool); ("estimator", Wrap_utils.Option.map estimator Np.Obj.to_pyobject); ("array", Some(array ))])

                  let check_is_fitted ?attributes ?msg ?all_or_any ~estimator () =
                     Py.Module.get_function_with_keywords __wrap_namespace "check_is_fitted"
                       [||]
                       (Wrap_utils.keyword_args [("attributes", Wrap_utils.Option.map attributes (function
| `S x -> Py.String.of_string x
| `Arr x -> Np.Obj.to_pyobject x
| `StringList x -> (Py.List.of_list_map Py.String.of_string) x
)); ("msg", Wrap_utils.Option.map msg Py.String.of_string); ("all_or_any", Wrap_utils.Option.map all_or_any (function
| `Callable x -> Wrap_utils.id x
| `PyObject x -> Wrap_utils.id x
)); ("estimator", Some(estimator |> Np.Obj.to_pyobject))])

let check_non_negative ~x ~whom () =
   Py.Module.get_function_with_keywords __wrap_namespace "check_non_negative"
     [||]
     (Wrap_utils.keyword_args [("X", Some(x |> Np.Obj.to_pyobject)); ("whom", Some(whom |> Py.String.of_string))])

let column_or_1d ?warn ~y () =
   Py.Module.get_function_with_keywords __wrap_namespace "column_or_1d"
     [||]
     (Wrap_utils.keyword_args [("warn", Wrap_utils.Option.map warn Py.Bool.of_bool); ("y", Some(y |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let label_binarize ?neg_label ?pos_label ?sparse_output ~y ~classes () =
   Py.Module.get_function_with_keywords __wrap_namespace "label_binarize"
     [||]
     (Wrap_utils.keyword_args [("neg_label", Wrap_utils.Option.map neg_label Py.Int.of_int); ("pos_label", Wrap_utils.Option.map pos_label Py.Int.of_int); ("sparse_output", Wrap_utils.Option.map sparse_output Py.Bool.of_bool); ("y", Some(y |> Np.Obj.to_pyobject)); ("classes", Some(classes |> Np.Obj.to_pyobject))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))
let logsumexp ?axis ?b ?keepdims ?return_sign ~a () =
   Py.Module.get_function_with_keywords __wrap_namespace "logsumexp"
     [||]
     (Wrap_utils.keyword_args [("axis", Wrap_utils.Option.map axis (fun ml -> Py.Tuple.of_list_map Py.Int.of_int ml)); ("b", Wrap_utils.Option.map b Np.Obj.to_pyobject); ("keepdims", Wrap_utils.Option.map keepdims Py.Bool.of_bool); ("return_sign", Wrap_utils.Option.map return_sign Py.Bool.of_bool); ("a", Some(a |> Np.Obj.to_pyobject))])
     |> (fun x -> (((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) (Py.Tuple.get x 0)), ((fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t)) (Py.Tuple.get x 1))))
let safe_sparse_dot ?dense_output ~a ~b () =
   Py.Module.get_function_with_keywords __wrap_namespace "safe_sparse_dot"
     [||]
     (Wrap_utils.keyword_args [("dense_output", dense_output); ("a", Some(a |> Np.Obj.to_pyobject)); ("b", Some(b ))])
     |> (fun py -> (Np.Obj.of_pyobject py : [>`ArrayLike] Np.Obj.t))