package modelkit

  1. Overview
  2. Docs
Portable classical machine learning workflows for OCaml

Install 

dune-project
 Dependency

github.com Readme Changelog Edit opam file Versions (4)

Authors

  1. A
    Asara

Maintainers

  1. A
    Asara developers <devs@asara.io>

Sources

modelkit-0.5.0.tbz
sha256=1fe8fa7c7f904dd098a21a2ca30fd69230750b8cf8aa2ae481b97a16531b47b4
sha512=c946cd1ac014726f4d21791e14d806a205680e6edfa2f80ed8d3680f24f48ca3c5a2f89d5afa68c11eac4053ead448b6381fb3d06dc8ff129097af6c69b262fb

doc/modelkit/Modelkit/Sample_weight/index.html

Module Modelkit.Sample_weight

Finite, non-negative sample weights aligned to samples.

At least one weight must be strictly positive.

type t
val create : expected_length:int -> Vector.t -> (t, Data_error.t) result
val of_array : expected_length:int -> float array -> (t, Data_error.t) result
val length : t -> int
val get : t -> int -> float
val to_vector : t -> Vector.t
val select : t -> Row_view.t -> (t, Data_error.t) result