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fabianp edited this page Sep 8, 2010 · 11 revisions

Some guidelines on writing documentation

Docstrings for estimators

The class should have a docstring with the fields Parameters, Attributes, Examples, See also. Example:

 class Foo (BaseEstimator):
    """
    C-Support Vector Classification.

    Parameters
    ----------

    C : float, optional (default=1.0)
        penalty parameter C of the error term.
    
    kernel : string, optional
         Description of this members.

    Attributes
    ----------

    `bar_` : array-like, shape = [n_features]
        Brief description of this attribute.



    Examples
    --------
    >>> clf = Foo()
    >>> clf.fit()
    []

    See also
    --------
    OtherClass
    """

The fit method

The fit method should also be documented, at least a description (even if it seems obvious) and the list of parameters. Something like

  def fit(self, X, Y):
      """
      Fit the SVM model according to the given training data and parameters.

      Parameters
      ----------
      X : array-like, shape = [n_samples, n_features]
          Training vector, where n_samples in the number of samples and
          n_features is the number of features.
      Y : array, shape = [n_samples]
          Target values (integers in classification, real numbers in
          regression)

      """
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