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let () = Wrap_utils.init ();;
let ns = Py.import "sklearn.dummy"
module BaseEstimator = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create () =
Py.Module.get_function_with_keywords ns "BaseEstimator"
[||]
[]
let get_params ?deep self =
Py.Module.get_function_with_keywords self "get_params"
[||]
(Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
let set_params ?params self =
Py.Module.get_function_with_keywords self "set_params"
[||]
(match params with None -> [] | Some x -> x)
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
module ClassifierMixin = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create () =
Py.Module.get_function_with_keywords ns "ClassifierMixin"
[||]
[]
let score ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "score"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> Ndarray.to_pyobject)); ("y", Some(y |> Ndarray.to_pyobject))])
|> Py.Float.to_float
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
module DummyClassifier = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create ?strategy ?random_state ?constant () =
Py.Module.get_function_with_keywords ns "DummyClassifier"
[||]
(Wrap_utils.keyword_args [("strategy", Wrap_utils.Option.map strategy Py.String.of_string); ("random_state", Wrap_utils.Option.map random_state (function
| `Int x -> Py.Int.of_int x
| `RandomState x -> Wrap_utils.id x
| `None -> Py.String.of_string "None"
)); ("constant", Wrap_utils.Option.map constant (function
| `Int x -> Py.Int.of_int x
| `String x -> Py.String.of_string x
| `Ndarray x -> Ndarray.to_pyobject x
))])
let fit ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "fit"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
))); ("y", Some(y |> Ndarray.to_pyobject))])
let get_params ?deep self =
Py.Module.get_function_with_keywords self "get_params"
[||]
(Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
let predict ~x self =
Py.Module.get_function_with_keywords self "predict"
[||]
(Wrap_utils.keyword_args [("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
)))])
|> Ndarray.of_pyobject
let predict_log_proba ~x self =
Py.Module.get_function_with_keywords self "predict_log_proba"
[||]
(Wrap_utils.keyword_args [("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
)))])
let predict_proba ~x self =
Py.Module.get_function_with_keywords self "predict_proba"
[||]
(Wrap_utils.keyword_args [("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
)))])
|> Ndarray.of_pyobject
let score ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "score"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `None -> Py.String.of_string "None"
))); ("y", Some(y |> Ndarray.to_pyobject))])
|> Py.Float.to_float
let set_params ?params self =
Py.Module.get_function_with_keywords self "set_params"
[||]
(match params with None -> [] | Some x -> x)
let classes_ self =
match Py.Object.get_attr_string self "classes_" with
| None -> raise (Wrap_utils.Attribute_not_found "classes_")
| Some x -> Ndarray.of_pyobject x
let n_classes_ self =
match Py.Object.get_attr_string self "n_classes_" with
| None -> raise (Wrap_utils.Attribute_not_found "n_classes_")
| Some x -> Wrap_utils.id x
let class_prior_ self =
match Py.Object.get_attr_string self "class_prior_" with
| None -> raise (Wrap_utils.Attribute_not_found "class_prior_")
| Some x -> Wrap_utils.id x
let n_outputs_ self =
match Py.Object.get_attr_string self "n_outputs_" with
| None -> raise (Wrap_utils.Attribute_not_found "n_outputs_")
| Some x -> Py.Int.to_int x
let sparse_output_ self =
match Py.Object.get_attr_string self "sparse_output_" with
| None -> raise (Wrap_utils.Attribute_not_found "sparse_output_")
| Some x -> Py.Bool.to_bool x
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
module DummyRegressor = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create ?strategy ?constant ?quantile () =
Py.Module.get_function_with_keywords ns "DummyRegressor"
[||]
(Wrap_utils.keyword_args [("strategy", Wrap_utils.Option.map strategy Py.String.of_string); ("constant", Wrap_utils.Option.map constant (function
| `Int x -> Py.Int.of_int x
| `Float x -> Py.Float.of_float x
| `Ndarray x -> Ndarray.to_pyobject x
)); ("quantile", quantile)])
let fit ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "fit"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
))); ("y", Some(y |> Ndarray.to_pyobject))])
let get_params ?deep self =
Py.Module.get_function_with_keywords self "get_params"
[||]
(Wrap_utils.keyword_args [("deep", Wrap_utils.Option.map deep Py.Bool.of_bool)])
let predict ?return_std ~x self =
Py.Module.get_function_with_keywords self "predict"
[||]
(Wrap_utils.keyword_args [("return_std", Wrap_utils.Option.map return_std Py.Bool.of_bool); ("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `PyObject x -> Wrap_utils.id x
)))])
|> Ndarray.of_pyobject
let score ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "score"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> (function
| `Ndarray x -> Ndarray.to_pyobject x
| `None -> Py.String.of_string "None"
))); ("y", Some(y |> Ndarray.to_pyobject))])
|> Py.Float.to_float
let set_params ?params self =
Py.Module.get_function_with_keywords self "set_params"
[||]
(match params with None -> [] | Some x -> x)
let constant_ self =
match Py.Object.get_attr_string self "constant_" with
| None -> raise (Wrap_utils.Attribute_not_found "constant_")
| Some x -> Ndarray.of_pyobject x
let n_outputs_ self =
match Py.Object.get_attr_string self "n_outputs_" with
| None -> raise (Wrap_utils.Attribute_not_found "n_outputs_")
| Some x -> Py.Int.to_int x
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
module MultiOutputMixin = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create () =
Py.Module.get_function_with_keywords ns "MultiOutputMixin"
[||]
[]
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
module RegressorMixin = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create () =
Py.Module.get_function_with_keywords ns "RegressorMixin"
[||]
[]
let score ?sample_weight ~x ~y self =
Py.Module.get_function_with_keywords self "score"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("X", Some(x |> Ndarray.to_pyobject)); ("y", Some(y |> Ndarray.to_pyobject))])
|> Py.Float.to_float
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end
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 ns "check_array"
[||]
(Wrap_utils.keyword_args [("accept_sparse", Wrap_utils.Option.map accept_sparse (function
| `String x -> Py.String.of_string x
| `Bool x -> Py.Bool.of_bool x
| `StringList x -> (Py.List.of_list_map Py.String.of_string) x
)); ("accept_large_sparse", Wrap_utils.Option.map accept_large_sparse Py.Bool.of_bool); ("dtype", Wrap_utils.Option.map dtype (function
| `String x -> Py.String.of_string x
| `Dtype x -> Wrap_utils.id x
| `TypeList x -> Wrap_utils.id x
| `None -> Py.String.of_string "None"
)); ("order", Wrap_utils.Option.map order (function
| `F -> Py.String.of_string "F"
| `C -> Py.String.of_string "C"
| `None -> Py.String.of_string "None"
)); ("copy", Wrap_utils.Option.map copy Py.Bool.of_bool); ("force_all_finite", Wrap_utils.Option.map force_all_finite (function
| `Bool x -> Py.Bool.of_bool x
| `Allow_nan -> Py.String.of_string "allow-nan"
)); ("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 (function
| `Bool x -> Py.Bool.of_bool x
| `None -> Py.String.of_string "None"
)); ("estimator", Wrap_utils.Option.map estimator (function
| `String x -> Py.String.of_string x
| `Estimator x -> Wrap_utils.id x
)); ("array", Some(array ))])
let check_consistent_length arrays =
Py.Module.get_function_with_keywords ns "check_consistent_length"
(Wrap_utils.pos_arg Wrap_utils.id arrays)
[]
let check_is_fitted ?attributes ?msg ?all_or_any ~estimator () =
Py.Module.get_function_with_keywords ns "check_is_fitted"
[||]
(Wrap_utils.keyword_args [("attributes", Wrap_utils.Option.map attributes (function
| `String x -> Py.String.of_string x
| `ArrayLike x -> Wrap_utils.id 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 ))])
let check_random_state ~seed () =
Py.Module.get_function_with_keywords ns "check_random_state"
[||]
(Wrap_utils.keyword_args [("seed", Some(seed |> (function
| `Int x -> Py.Int.of_int x
| `RandomState x -> Wrap_utils.id x
| `None -> Py.String.of_string "None"
)))])
let class_distribution ?sample_weight ~y () =
Py.Module.get_function_with_keywords ns "class_distribution"
[||]
(Wrap_utils.keyword_args [("sample_weight", Wrap_utils.Option.map sample_weight Ndarray.to_pyobject); ("y", Some(y ))])
|> (fun x -> ((Wrap_utils.id (Py.Tuple.get x 0)), (Wrap_utils.id (Py.Tuple.get x 1)), (Wrap_utils.id (Py.Tuple.get x 2))))
module Deprecated = struct
type t = Py.Object.t
let of_pyobject x = x
let to_pyobject x = x
let create ? () =
Py.Module.get_function_with_keywords ns "deprecated"
[||]
(Wrap_utils.keyword_args [("extra", Wrap_utils.Option.map extra Py.String.of_string)])
let to_string self = Py.Object.to_string self
let show self = to_string self
let pp formatter self = Format.fprintf formatter "%s" (show self)
end