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Data Discretization with Chi-Squared Test
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:doc:`/SingleStepClassifiers/CausalStep/index`

This step first preforms an initial discretization for the input discrete data, then repeats a bottom-up merging process continuously until a termination condition is fulfilled. The merging process consists of two steps: (1) perform the Chi-squared test for each pair of adjacent intervals, (2) merge the pair of adjacent intervals with the lowest Chi-square value. Merging continues until all pairs. For details refer to the `ChiMerge algorithm <http://sci2s.ugr.es/keel/pdf/algorithm/congreso/1992-Kerber-ChimErge-AAAI92.pdf>`__.

.. rubric:: Input Parameters

1. Input data

2. Chi-squared significance threshold

.. rubric:: Output Parameters

1. Discretized data

.. rubric:: Workflow

.. image:: workflow.svg


.. rubric:: Algorithm

:doc:`/Algorithms/ChiSquaredTest/index`

.. rubric:: References

- R.\  Kerber, ChiMerge: Discretization of Numeric Attributes, Learning: Inductive, AAAI 92, pp. 123-128, 1992.