Changeset 7621:65739376d4a0 in orange


Ignore:
Timestamp:
02/08/11 15:40:18 (3 years ago)
Author:
janezd <janez.demsar@…>
Branch:
default
Convert:
0ba114781760d7b1e24fd32a8621bb780d164441
Message:

Minor fixes in documentation

Location:
orange
Files:
2 edited

Legend:

Unmodified
Added
Removed
  • orange/Orange/statistics/distributions.py

    r7619 r7621  
    2121    .. attribute:: variable 
    2222     
    23         The descriptor for the feature to which the data applies. 
     23        Descriptor for the variable to which the data applies. 
    2424 
    2525    .. attribute:: min, max 
    2626 
    27         Minimal and maximal feature value encountered 
    28         in the data table. 
     27        Minimal and maximal variable value encountered. 
    2928 
    3029    .. attribute:: avg, dev 
     
    5049    .. method:: add(value[, weight=1]) 
    5150     
     51        Add a value to the statistics. 
     52 
    5253        :param value: Value to be added to the statistics 
    5354        :type value: float 
     
    5556        :type weight: float 
    5657 
    57         Adds a value to the statistics. 
    58  
    5958    .. 
    6059        .. method:: recompute() 
    6160 
    62             Recomputes the average and deviation. 
     61            Recompute the average and deviation. 
    6362 
    6463    The class works as follows. Values are added by :obj:`add`, for each value 
     
    7978 
    8079    .. method:: __init__(data[, weight=None]) 
     80 
     81        Compute the statistics for all continuous features in the 
     82        give data, and put `None` to the places corresponding to features of other types. 
    8183 
    8284        :param data: A table of instances 
     
    8587        :type weight: `int` or none 
    8688         
    87         Constructor computes the statistics for all continuous features in the 
    88         give data, and puts `None` to the places corresponding to other types of 
    89         features. 
    90      
    9189    .. method:: purge() 
    9290     
    93         Removes the ``None``'s corresponding to non-continuous features. 
     91        Remove the ``None``'s corresponding to non-continuous features. 
    9492     
    9593    part of `distributions-basic-stat.py`_ (uses monks-1.tab) 
     
    191189    .. method:: __init__(outerVariable, innerVariable) 
    192190      
     191        Construct an instance of ``Contingency`` for the given pair of 
     192        variables. 
     193      
    193194        :param outerVariable: Descriptor of the outer variable 
    194195        :type outerVariable: Orange.data.feature.Feature 
     
    196197        :type innerVariable: Orange.data.feature.Feature 
    197198         
    198         Construct an instance of ``Contingency`` for the given pair of 
    199         variables. 
    200       
    201199    .. method:: add(outer_value, inner_value[, weight=1]) 
    202200     
     201        Add an element to the contingency matrix by adding 
     202        ``weight`` to the corresponding cell. 
     203 
    203204        :param outer_value: The value for the outer variable 
    204205        :type outer_value: int, float, string or :obj:`Orange.data.Value` 
     
    207208        :param weight: Instance weight 
    208209        :type weight: float 
    209  
    210         Add an element to the contingency matrix by adding 
    211         ``weight`` to the corresponding cell. 
    212210 
    213211    .. method:: normalize() 
     
    283281        This is always equal either to innerVariable or outerVariable 
    284282 
    285     .. method:: add_attrclass(attribute_value, class_value[, weight]) 
     283    .. method:: add_attrclass(variable_value, class_value[, weight]) 
    286284 
    287285        Adds an element to contingency. The difference between this and 
    288         Contigency.add is that the feature value is always the first 
    289         argument and class value the second, regardless whether the feature 
    290         is actually the outer variable or the inner.  
     286        Contigency.add is that the variable value is always the first 
     287        argument and class value the second, regardless of what is inner and 
     288        outer.  
     289 
     290        :param attribute_value: Variable value 
     291        :type attribute_value: int, float, string or :obj:`Orange.data.Value` 
     292        :param class_value: Class value 
     293        :type class_value: int, float, string or :obj:`Orange.data.Value` 
     294        :param weight: Instance weight 
     295        :type weight: float 
    291296 
    292297 
     
    305310    .. method:: __init__(feature, class_attribute) 
    306311 
     312        Construct an instance of :obj:`ContingencyVarClass` for the given pair of 
     313        variables. Inherited from :obj:`Contingency`. 
     314 
    307315        :param outerVariable: Descriptor of the outer variable 
    308316        :type outerVariable: Orange.data.feature.Feature 
     
    310318        :type innerVariable: Orange.data.feature.Feature 
    311319         
    312         Construct an instance of :obj:`ContingencyVarClass` for the given pair of 
    313         variables. Inherited from :obj:`Contingency`. 
    314  
    315320    .. method:: __init__(feature, data[, weightId]) 
     321 
     322        Compute the contingency from the given instances.      
    316323 
    317324        :param feature: Descriptor of the outer variable 
     
    322329        :type weightId: int 
    323330 
    324         Compute the contingency from the given instances.      
    325  
    326331    .. method:: p_class(value) 
     332 
     333        Return the probability distribution of classes given the value of the 
     334        variable. Equivalent to `self[value]`, except for normalization. 
    327335 
    328336        :param value: The value of the variable 
    329337        :type value: int, float, string or :obj:`Orange.data.Value` 
    330338 
    331         Return the probability distribution of classes given the value of the 
    332         variable. Equivalent to `self[value]`, except for normalization. 
    333  
    334339    .. method:: p_class(value, class_value) 
    335340 
     341        Returns the conditional probability of the class_value given the 
     342        feature value, p(class_value|value) (note the order of arguments!) 
     343        Equivalent to `self[values][class_value]`, except for normalization. 
     344         
    336345        :param value: The value of the variable 
    337346        :type value: int, float, string or :obj:`Orange.data.Value` 
     
    339348        :type value: int, float, string or :obj:`Orange.data.Value` 
    340349 
    341         Returns the conditional probability of the class_value given the 
    342         feature value, p(class_value|value) (note the order of arguments!) 
    343         Equivalent to `self[values][class_value]`, except for normalization. 
    344          
    345350    .. _distributions-contingency3.py: code/distributions-contingency3.py 
    346351 
     
    395400    .. method:: __init__(feature, class_attribute) 
    396401 
     402        Construct an instance of :obj:`ContingencyVarClass` for the given pair of 
     403        variables. Inherited from :obj:`Contingency`, except for the reversed 
     404        order. 
     405 
    397406        :param outerVariable: Descriptor of the outer variable 
    398407        :type outerVariable: Orange.data.feature.Feature 
     
    400409        :type innerVariable: Orange.data.feature.Feature 
    401410         
    402         Construct an instance of :obj:`ContingencyVarClass` for the given pair of 
    403         variables. Inherited from :obj:`Contingency`, except for the reversed 
    404         order. 
    405  
    406411    .. method:: __init__(feature, instances[, weightId]) 
     412 
     413        Compute the contingency from the given instances.      
    407414 
    408415        :param feature: Descriptor of the outer variable 
     
    413420        :type weightId: int 
    414421 
    415         Compute the contingency from the given instances.      
    416  
    417422    .. method:: p_attr(class_value) 
     423 
     424        Return the probability distribution of variable given the class. 
     425        Equivalent to `self[class_value]`, except for normalization. 
    418426 
    419427        :param class_value: The value of the variable 
    420428        :type class_value: int, float, string or :obj:`Orange.data.Value` 
    421429 
    422         Return the probability distribution of variable given the class. 
    423         Equivalent to `self[class_value]`, except for normalization. 
    424  
    425430    .. method:: p_attr(value, class_value) 
     431 
     432        Returns the conditional probability of the value given the 
     433        class, p(value|class_value). 
     434        Equivalent to `self[class][value]`, except for normalization. 
    426435 
    427436        :param value: The value of the variable 
     
    430439        :type value: int, float, string or :obj:`Orange.data.Value` 
    431440 
    432         Returns the conditional probability of the value given the 
    433         class, p(value|class_value). 
    434         Equivalent to `self[class][value]`, except for normalization. 
    435  
    436441    .. _distributions-contingency4.py: code/distributions-contingency4.py 
    437442     
     
    474479 
    475480    .. method:: __init__(outer_variable, inner_variable, data[, weightId]) 
     481 
     482        Compute the contingency from the given instances. 
    476483 
    477484        :param outer_variable: Descriptor of the outer variable 
     
    484491        :type weightId: int 
    485492 
    486         Compute the contingency from the given instances. 
    487  
    488493    .. method:: p_attr(outer_value) 
    489494 
     
    491496        variable given the outer variable value. 
    492497 
     498        :param outer_value: The value of the outer variable 
     499        :type outer_value: int, float, string or :obj:`Orange.data.Value` 
     500  
    493501    .. method:: p_attr(outer_value, inner_value) 
    494502 
     
    496504        given the outer_value. 
    497505 
     506        :param outer_value: The value of the outer variable 
     507        :type outer_value: int, float, string or :obj:`Orange.data.Value` 
     508        :param inner_value: The value of the inner variable 
     509        :type inner_value: int, float, string or :obj:`Orange.data.Value` 
    498510 
    499511    The following example investigates which material is used for 
  • orange/doc/sphinx-ext/themes/orange_theme/static/orange.css

    r7619 r7621  
    293293    margin-left: -5px; 
    294294    margin-bottom: 20px; 
     295    margin-top: 40px; 
    295296} 
    296297 
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