package sklearn

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in-package search v0.2.0

package sklearn

sklearn
- Sklearn

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module ABCMeta : sig ... end

module BaseEstimator : sig ... end

val abstractmethod : funcobj:Py.Object.t -> unit -> Py.Object.t

A decorator indicating abstract methods.

Requires that the metaclass is ABCMeta or derived from it. A class that has a metaclass derived from ABCMeta cannot be instantiated unless all of its abstract methods are overridden. The abstract methods can be called using any of the normal 'super' call mechanisms.

Usage:

class C(metaclass=ABCMeta): @abstractmethod def my_abstract_method(self, ...): ...

val if_delegate_has_method : 
  delegate:
    [ `String of string
    | `StringList of string list
    | `PyObject of Py.Object.t ] ->
  unit ->
  Py.Object.t

Create a decorator for methods that are delegated to a sub-estimator

This enables ducktyping by hasattr returning True according to the sub-estimator.

Parameters ---------- delegate : string, list of strings or tuple of strings Name of the sub-estimator that can be accessed as an attribute of the base object. If a list or a tuple of names are provided, the first sub-estimator that is an attribute of the base object will be used.

val update_wrapper : 
  ?assigned:Py.Object.t ->
  ?updated:Py.Object.t ->
  wrapper:Py.Object.t ->
  wrapped:Py.Object.t ->
  unit ->
  Py.Object.t

Update a wrapper function to look like the wrapped function

wrapper is the function to be updated wrapped is the original function assigned is a tuple naming the attributes assigned directly from the wrapped function to the wrapper function (defaults to functools.WRAPPER_ASSIGNMENTS) updated is a tuple naming the attributes of the wrapper that are updated with the corresponding attribute from the wrapped function (defaults to functools.WRAPPER_UPDATES)