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  • docs/reference/rst/Orange.data.discretization.rst

    r10393 r11477  
    7171.. autoclass:: DiscretizeTable(features=None, discretize_class=False, method=EqualFreq(n=3), clean=True) 
    73 .. A chapter on `feature subset selection <../ofb/o_fss.htm>`_ in Orange 
     73.. A chapter on feature subset selection in Orange 
    7474   for Beginners tutorial shows the use of DiscretizedLearner. Other 
    7575   discretization classes from core Orange are listed in chapter on 
    76    `categorization <../ofb/o_categorization.htm>`_ of the same tutorial. -> should put in classification/wrappers 
     76   categorization of the same tutorial. -> should put in classification/wrappers 
    7878.. [FayyadIrani1993] UM Fayyad and KB Irani. Multi-interval discretization of continuous valued 
  • docs/widgets/rst/visualize/polyviz.rst

    r11359 r11477  
    5252See the documentation on :ref:`Radviz` for details on various aspects 
    5353controlled by the :obj:`Settings` tab. The utility of VizRank, an intelligent 
    54 visualization technique, using `brown-selected.tab 
    55 <http://orange.biolab.si/doc/datasets/brown-selected.tab>`_ data set is 
     54visualization technique, using brown-selected.tab data set is 
    5655illustrated with a snapshot below. 
  • docs/widgets/rst/visualize/scatterplot.rst

    r11422 r11477  
    7373optimization is to find those scatterplot projections, where instances with 
    7474different class labels are well separated. For example, for a data set  
    75 `brown-selected.tab <http://orange.biolab.si/doc/datasets/brown-selected.tab>`_ 
    7676(comes with Orange installation) the two attributes that best separate 
    7777instances of different class are displayed in the snapshot below, where we have 
    148148outliers. The idea is that the outliers are those data instances, which are 
    149149incorrectly classified in many of the top visualizations. For example, the 
    150 class of the 33-rd instance in `brown-selected.tab 
    151 <http://orange.biolab.si/doc/datasets/brown-selected.tab>`_ should be Resp, 
     150class of the 33-rd instance in brown-selected.tab should be Resp, 
    152151but this instance is quite often misclassified as Ribo. The snapshot below 
    153152shows one particular visualization displaying why such misclassification 
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