package sklearn

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package sklearn
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type tag = [
  1. | `OutlierMixin
]
type t = [ `Object | `OutlierMixin ] Obj.t
val of_pyobject : Py.Object.t -> t
val to_pyobject : [> tag ] Obj.t -> Py.Object.t
val create : unit -> t

Mixin class for all outlier detection estimators in scikit-learn.

val fit_predict : ?y:Py.Object.t -> x:[> `ArrayLike ] Np.Obj.t -> [> tag ] Obj.t -> [> `ArrayLike ] Np.Obj.t

Perform fit on X and returns labels for X.

Returns -1 for outliers and 1 for inliers.

Parameters ---------- X : array-like, sparse matrix, dataframe of shape (n_samples, n_features)

y : Ignored Not used, present for API consistency by convention.

Returns ------- y : ndarray of shape (n_samples,) 1 for inliers, -1 for outliers.

val to_string : t -> string

Print the object to a human-readable representation.

val show : t -> string

Print the object to a human-readable representation.

val pp : Stdlib.Format.formatter -> t -> unit

Pretty-print the object to a formatter.