Distribution and variable precision local reduction method of decision table
A decision table and decision-making technology, applied in the fields of pattern recognition and machine learning, knowledge discovery, and data mining, can solve problems such as high computational complexity, achieve the effect of improving computational efficiency and reducing computational complexity
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Embodiment 1
[0069] Such as figure 1 As shown, the local attribute reduction method of the decision table distribution matrix provided by the embodiment of the present invention does not change, including:
[0070] S11, acquiring decision table data;
[0071] S12. Determine a certain decision class for local attribute reduction according to the acquired decision table data;
[0072] S13, calculating the local distribution matrix of the decision class;
[0073] S14. Calculate the resolution matrix of the decision class according to the preset definition of local attribute distribution reduction and obtain the local distribution matrix of the decision class;
[0074] S15. According to the obtained resolution matrix, convert the corresponding resolution function from the principal conjunctive normal form to the principal disjunctive normal form to obtain all the reduction results.
[0075] The local attribute reduction method of the decision table distribution matrix described in the embod...
Embodiment 2
[0096] Such as figure 2 As shown, the embodiment of the present invention also provides a local attribute reduction method with the decision table intercept matrix unchanged, including:
[0097] S21, acquiring decision table data;
[0098] S22. Determine a decision class for local attribute reduction according to the acquired decision table data;
[0099] S23, calculating the local distribution matrix of the decision class;
[0100] S24. Calculate the β-section matrix of the local distribution matrix, where β is a preset value, and the range of values is (0,1];
[0101] S25. Calculate the resolution matrix of the decision class according to the preset definition of variable precision reduction of local attributes and the obtained β-section matrix;
[0102] S26. According to the obtained resolution matrix, convert the corresponding resolution function from the principal conjunctive normal form to the principal disjunctive normal form to obtain all reduction results.
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