package modelkit

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package modelkit
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Module Modelkit.Simple_imputer

Column-wise replacement of NaN missing values.

Mean and median fitting fail when a training feature contains no observed value. Constant values must be finite. Transform rejects infinities and preserves the input feature schema. Sample weights are rejected. Mean fitting is O(rows * columns); median fitting is O(columns * rows * log rows) with one temporary column allocation.

type strategy =
  1. | Mean
  2. | Median
  3. | Constant of float
type params = {
  1. strategy : strategy;
}
type t
type fitted
val mean : unit -> t
val median : unit -> t
val constant : float -> (t, Error.t) result
val statistics : fitted -> Vector.t
include TRANSFORMER with type t := t and type params := params and type target = unit and type fitted := fitted and type rng = Rng.t
include SPECIFICATION with type t := t with type params := params
val clone : t -> t
val params : t -> params
type target = unit
type rng = Rng.t
val fit : t -> ?sample_weight:Sample_weight.t -> rng:rng -> feature_schema:Feature_schema.t -> x:Matrix.t -> y:target option -> unit -> (fitted, Error.t) result
val transform : fitted -> feature_schema:Feature_schema.t -> x:Matrix.t -> (Matrix.t, Error.t) result
val fitted_params : fitted -> params
val input_schema : fitted -> Feature_schema.t
val output_schema : fitted -> Feature_schema.t