package sklearn

You can search for identifiers within the package.

in-package search v0.2.0

package sklearn

sklearn
- Sklearn

Legend:
Library
Module
Module type
Parameter
Class
Class type

val get_py : string -> Py.Object.t

Get an attribute of this module as a Py.Object.t. This is useful to pass a Python function to another function.

module DictVectorizer : sig ... end

module FeatureHasher : sig ... end

module Image : sig ... end

module Text : sig ... end

val grid_to_graph : 
  ?n_z:int ->
  ?mask:Py.Object.t ->
  ?return_as:Py.Object.t ->
  ?dtype:Np.Dtype.t ->
  n_x:int ->
  n_y:int ->
  unit ->
  Py.Object.t

Graph of the pixel-to-pixel connections

Edges exist if 2 voxels are connected.

Parameters ---------- n_x : int Dimension in x axis n_y : int Dimension in y axis n_z : int, optional, default 1 Dimension in z axis mask : ndarray of booleans, optional An optional mask of the image, to consider only part of the pixels. return_as : np.ndarray or a sparse matrix class, optional The class to use to build the returned adjacency matrix. dtype : dtype, optional, default int The data of the returned sparse matrix. By default it is int

Notes ----- For scikit-learn versions 0.14.1 and prior, return_as=np.ndarray was handled by returning a dense np.matrix instance. Going forward, np.ndarray returns an np.ndarray, as expected.

For compatibility, user code relying on this method should wrap its calls in ``np.asarray`` to avoid type issues.

val img_to_graph : 
  ?mask:Py.Object.t ->
  ?return_as:Py.Object.t ->
  ?dtype:Np.Dtype.t ->
  img:[ `Arr of [> `ArrayLike ] Np.Obj.t | `PyObject of Py.Object.t ] ->
  unit ->
  Py.Object.t

Graph of the pixel-to-pixel gradient connections

Edges are weighted with the gradient values.

Read more in the :ref:`User Guide <image_feature_extraction>`.

Parameters ---------- img : ndarray, 2D or 3D 2D or 3D image mask : ndarray of booleans, optional An optional mask of the image, to consider only part of the pixels. return_as : np.ndarray or a sparse matrix class, optional The class to use to build the returned adjacency matrix. dtype : None or dtype, optional The data of the returned sparse matrix. By default it is the dtype of img

Notes ----- For scikit-learn versions 0.14.1 and prior, return_as=np.ndarray was handled by returning a dense np.matrix instance. Going forward, np.ndarray returns an np.ndarray, as expected.

For compatibility, user code relying on this method should wrap its calls in ``np.asarray`` to avoid type issues.