Changeset 8924:b144cc5cf18e in orange


Ignore:
Timestamp:
09/08/11 10:51:58 (3 years ago)
Author:
ales_erjavec <ales.erjavec@…>
Branch:
default
Convert:
0e446298a002cf7ad39824f41b22bf19ce92ba70
Message:

Fixed pls sphinx documentation warnings.

Location:
orange
Files:
1 added
2 edited

Legend:

Unmodified
Added
Removed
  • orange/Orange/regression/pls.py

    r8923 r8924  
    88.. _`Parital Least Squares Regression`: http://en.wikipedia.org/wiki/Partial_least_squares_regression 
    99 
    10 Implementation is based on _`Scikit learn python implementation`: https://github.com/scikit-learn/scikit-learn/blob/master/scikits/learn/pls.py 
     10Implementation is based on `Scikit learn python implementation`_ 
    1111 
    1212Example :: 
     
    5151.. autofunction:: svd_xy 
    5252 
     53.. _`Scikit learn python implementation`: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/pls.py 
     54 
    5355""" 
    5456 
     
    6264 
    6365def normalize_matrix(X): 
    64     """Normalizes matrix, i.e. subtracts column means 
     66    """ Normalizes matrix, i.e. subtracts column means 
    6567    and divides them by column standard deviations. 
    6668    Returns the standardized matrix, sample mean and 
     
    8991 
    9092    :param tol: tolerance parameter, if norm of difference 
    91     between two successive left singular vectors is less than tol, 
    92     iteration is stopped 
     93        between two successive left singular vectors is less than tol, 
     94        iteration is stopped 
    9395    :type tol: a not negative float 
    9496             
     
    132134 
    133135def svd_xy(X, Y): 
    134     """Returns the first left and rigth singular 
     136    """ Returns the first left and rigth singular 
    135137    vectors of X'Y. 
    136138 
     
    145147 
    146148class PLSRegressionLearner(base.BaseRegressionLearner): 
    147  
    148     """Fits the partial least squares regression model, 
     149    """ Fits the partial least squares regression model, 
    149150    i.e. learns the regression parameters. The implementation is based on 
    150     _`Scikit learn python implementation`: 
    151     https://github.com/scikit-learn/scikit-learn/blob/master/scikits/learn/pls.py 
     151    `Scikit learn python implementation`_ 
    152152     
    153153    The class is derived from 
     
    241241 
    242242        :param xVars, yVars: List of input and response variables 
    243         (`Orange.data.variable.Continuous` or `Orange.data.variable.Continuous`). 
    244         If None (default) it is assumed that data definition provides information 
    245         which variables are reponses and which not. If a variable var 
    246         has key "label" in dictionary Orange.data.Domain[var].attributes 
    247         it is treated as a response variable 
     243            (`Orange.data.variable.Continuous` or `Orange.data.variable.Continuous`). 
     244            If None (default) it is assumed that data definition provides information 
     245            which variables are reponses and which not. If a variable var 
     246            has key "label" in dictionary Orange.data.Domain[var].attributes 
     247            it is treated as a response variable 
    248248        :type xVars, yVars: list             
    249249 
     
    376376 
    377377class PLSRegression(Orange.classification.Classifier): 
    378     """PLSRegression predicts value of the response variables 
     378    """ PLSRegression predicts value of the response variables 
    379379    based on the values of independent variables. 
    380380    """ 
     
    393393        """ 
    394394        :param instance: data instance for which the value of the response 
    395         variable will be predicted 
     395            variable will be predicted 
    396396        :type instance:  
    397397        """  
     
    421421             
    422422    def print_pls_regression_coefficients(self): 
    423         """Pretty-prints the coefficient of the PLS regression model. 
     423        """ Pretty-prints the coefficient of the PLS regression model. 
    424424        """        
    425425        xVars, yVars = [x.name for x in self.xVars], [y.name for y in self.yVars] 
  • orange/doc/Orange/rst/Orange.regression.rst

    r8793 r8924  
    1010   Orange.regression.linear 
    1111   Orange.regression.lasso 
     12   Orange.regression.pls 
    1213   Orange.regression.earth 
    1314   Orange.regression.tree 
Note: See TracChangeset for help on using the changeset viewer.