Changeset 9544:b432bd8bfe4b in orange


Ignore:
Timestamp:
01/18/12 09:43:13 (2 years ago)
Author:
lanz <lan.zagar@…>
Branch:
default
Convert:
7bc101cd61cc76bdffea5bd0d6932ff551f4a3d9
Message:

Documentation improvements for multitarget.tree

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1 edited

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  • orange/Orange/multitarget/tree.py

    r9536 r9544  
    88To use the tree learning algorithm for multi-target data, standard 
    99orange trees (:class:`Orange.classification.tree.TreeLearner`) can be used. 
    10 Only the :obj:`Orange.classification.tree.TreeLearner.measure` for feature 
    11 scoring and the :obj:`Orange.classification.tree.TreeLearner.node_learner` 
     10Only the :obj:`~Orange.classification.tree.TreeLearner.measure` for feature 
     11scoring and the :obj:`~Orange.classification.tree.TreeLearner.node_learner` 
    1212components have to be chosen so that they work on multi-target data domains. 
    1313 
    1414This module provides one such measure (:class:`MultitargetVariance`) that 
    1515can be used and a helper class :class:`MultiTreeLearner` which extends 
    16 :class:`Orange.classification.tree.TreeLearner` and is the same in all 
    17 aspects except for different (multi-target) defaults for `measure` and 
    18 `node_learner`. 
     16:class:`~Orange.classification.tree.TreeLearner` and is the same in all 
     17aspects except for different (multi-target) defaults for 
     18:obj:`~Orange.classification.tree.TreeLearner.measure` and 
     19:obj:`~Orange.classification.tree.TreeLearner.node_learner`. 
    1920 
    2021Examples 
     
    9697        :type data: :class:`Orange.data.Table` 
    9798 
    98         :return: :obj:`list` of tuples (threshold, score, None) 
     99        :return: :obj:`list` of :obj:`tuples <tuple>` [(threshold, score, None),] 
    99100        """ 
    100101 
     
    151152    """ 
    152153    MultiTreeLearner is a multi-target version of a tree learner. It is the 
    153     same as :class:`Orange.classification.tree.TreeLearner`, except for the 
     154    same as :class:`~Orange.classification.tree.TreeLearner`, except for the 
    154155    default values of two parameters: 
    155156     
    156157    .. attribute:: measure 
    157158         
    158         A multi-target score is used by default: :class:`Orange.multitarget.tree.MultitargetVariance`. 
     159        A multi-target score is used by default: :class:`MultitargetVariance`. 
    159160 
    160161    .. attribute:: node_learner 
    161162         
    162         Standard trees use :class:`Orange.classification.majority.MajorityLearner` 
     163        Standard trees use :class:`~Orange.classification.majority.MajorityLearner` 
    163164        to construct prediction models in the leaves of the tree. 
    164165        MultiTreeLearner uses the multi-target equivalent which can be  
     
    171172    def __init__(self, **kwargs): 
    172173        """ 
    173         The constructor simply passes all given arguments to TreeLearner's constructor 
     174        The constructor simply passes all given arguments to 
     175        :class:`~Orange.classification.tree.TreeLearner`'s constructor 
    174176        :obj:`Orange.classification.tree.TreeLearner.__init__`. 
    175177        """ 
     
    203205    """ 
    204206    MultiTree classifier is almost the same as the base class it extends 
    205     (:class:`Orange.classification.tree.TreeClassifier`). Only the 
     207    (:class:`~Orange.classification.tree.TreeClassifier`). Only the 
    206208    :obj:`__call__` method is modified so it works with multi-target data. 
    207209    """ 
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