Ignore:
Timestamp:
02/27/13 15:02:50 (14 months ago)
Author:
Ales Erjavec <ales.erjavec@…>
Branch:
default
Message:

Cleanup of 'Widget catalog' documentation.

Fixed rst text formating, replaced dead hardcoded reference links (now using
:ref:), etc.

File:
1 edited

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  • docs/widgets/rst/regression/pade.rst

    r11050 r11359  
    66.. image:: ../icons/Pade.png 
    77 
    8 Replaces a continuous class with a derivative or a MQC by one or more continuous attributes. 
     8Replaces a continuous class with a derivative or a MQC by one or more 
     9continuous attributes. 
    910 
    1011Signals 
     
    2425----------- 
    2526 
    26 This widget implements several techniques for assessing partial derivatives of the class variable for the given set of examples. The derivative is appended to the example table as a new class attribute. The widget can compute either quantitative derivative by a chosen continuous attribute or a qualitative derivative by one or more attributes. 
     27This widget implements several techniques for assessing partial derivatives 
     28of the class variable for the given set of examples. The derivative is appended 
     29to the example table as a new class attribute. The widget can compute either 
     30quantitative derivative by a chosen continuous attribute or a qualitative 
     31derivative by one or more attributes. 
    2732 
    28 The widget is implemented to cache some data. After, for instance, computing the derivatives by :code:`x`and :code:`y` separately, the widget has already stored all the data to produce the derivatives by both in a moment. 
     33The widget is implemented to cache some data. After, for instance, computing 
     34the derivatives by :code:`x` and :code:`y` separately, the widget has already 
     35stored all the data to produce the derivatives by both in a moment. 
    2936 
    3037.. image:: images/Pade.png 
    3138 
    32 The :obj:`Attributes` box lists all continuous attributes and lets the user select the attribute by which she wants to compute the qualitative derivative. The selection is important only when the widget actually outputs a qualitative derivative (this depends on other settings, described below). Buttons :obj:`All` and :obj:`None` select the entire list and nothing. 
     39The :obj:`Attributes` box lists all continuous attributes and lets the user 
     40select the attribute by which she wants to compute the qualitative derivative. 
     41The selection is important only when the widget actually outputs a qualitative 
     42derivative (this depends on other settings, described below). Buttons 
     43:obj:`All` and :obj:`None` select the entire list and nothing. 
    3344 
    34 Derivatives by more than one attribute are mathematically questionable, and computing by many attributes can be slow and messy. Methods that are based on triangulation will include all attributes in the triangulation, regardless of the selection, but then compute only the selected derivatives. 
     45Derivatives by more than one attribute are mathematically questionable, and 
     46computing by many attributes can be slow and messy. Methods that are based on 
     47triangulation will include all attributes in the triangulation, regardless of 
     48the selection, but then compute only the selected derivatives. 
    3549 
    36 Box :obj:`Method` determines the used method and its settings. Available methods are :obj:`First triangle`, :obj:`Star Regression`, :obj:`Univariate Star Regression` and :obj:`Tube Regression`. First triangle is unsuitable for data with non-negligible noise. Star regression seems to perform rather poor; the quantitative derivatives it computes are even theoretically wrong. Univariate Star Regression will handle noise well, but also work well for very complex functions (like sin(x)sin(y) across several periods). Tube regression is very noise resistant, which can lead it to oversimplify the model, yet it is the only method that does not use the triangulation and is thus capable of handling discrete attributes, unknown values and large number of dimensions. It may be slow when the number of examples is very large. Detailed description of these methods can be found in Zabkar and Demsar's papers. 
     50Box :obj:`Method` determines the used method and its settings. Available 
     51methods are :obj:`First triangle`, :obj:`Star Regression`, 
     52:obj:`Univariate Star Regression` and :obj:`Tube Regression`. First triangle is 
     53unsuitable for data with non-negligible noise. Star regression seems to perform 
     54rather poor; the quantitative derivatives it computes are even theoretically 
     55wrong. Univariate Star Regression will handle noise well, but also work well 
     56for very complex functions (like sin(x)sin(y) across several periods). Tube 
     57regression is very noise resistant, which can lead it to oversimplify the 
     58model, yet it is the only method that does not use the triangulation and is 
     59thus capable of handling discrete attributes, unknown values and large number 
     60of dimensions. It may be slow when the number of examples is very large. 
     61Detailed description of these methods can be found in Zabkar and Demsar's 
     62papers. 
    3763 
    38 :obj:`Ignore differences below` lets the user set a threshold for qualitative derivatives. 
     64:obj:`Ignore differences below` lets the user set a threshold for qualitative 
     65derivatives. 
    3966 
    40 The widget can also put some data in meta attributes: the :obj:`Qualitative constraint`, as described above, :obj:`Derivatives of selected attributes` and the :obj:`Original class attribute`. 
     67The widget can also put some data in meta attributes: the 
     68:obj:`Qualitative constraint`, as described above, 
     69:obj:`Derivatives of selected attributes` and the 
     70:obj:`Original class attribute`. 
    4171 
    42 The changes take effect and the widget start processing when :obj:`Apply` is hit. 
     72The changes take effect and the widget start processing when :obj:`Apply` 
     73is hit. 
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