<th id="5nh9l"></th><strike id="5nh9l"></strike><th id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"></th><strike id="5nh9l"></strike>
<progress id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"><noframes id="5nh9l">
<th id="5nh9l"></th> <strike id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"></span>
<progress id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"></span><strike id="5nh9l"><noframes id="5nh9l"><strike id="5nh9l"></strike>
<span id="5nh9l"><noframes id="5nh9l">
<span id="5nh9l"><noframes id="5nh9l">
<span id="5nh9l"></span><span id="5nh9l"><video id="5nh9l"></video></span>
<th id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"></th>
<progress id="5nh9l"><noframes id="5nh9l">

基于Skowron分明矩陣的有效屬性約簡算法

Efficient algorithm of attribute reduction based on Skowron's discernibility matrix

  • 摘要: 為降低基于Skowron分明矩陣屬性約簡算法的復雜度,提出了簡化分明矩陣及其相應屬性約簡的定義,并證明了基于簡化分明矩陣的屬性約簡與基于原分明矩陣的屬性約簡等價.在簡化決策表的基礎上,定義了一個函數,該函數能度量條件屬性在簡化分明矩陣中出現的頻率,并給出了計算該函數的快速算法,其時間和空間復雜度均為O(|U/C|).用該函數設計了一個有效的基于原分明矩陣屬性約簡算法,算法的時間復雜度降為O(|C||U|)+O(|C|2|U/C|),空間復雜度降為O(|U|);并用實例證明了算法的有效性.

     

    Abstract: To cut down the time and space complexity and improve the efficiency of the attribute reduction algorithm based on Skowron's discernibility matrix, the definitions of a simplified discernibility matrix and corresponding attribute reduction were provided. It is proved that attribute reduction based on the simplified discernibility matrix is equivalent to that based on the old one. By the foundation of a simplified decision table, a function which can measure the frequency of a condition attribute in the simplified discernibility matrix was defined. An algorithm for the above function was designed. Its time and space complexity are O (|U/C|). Then an efficient algorithm of attribute reduction based on Skowron's discernibility matrix was designed with the new function. Its time complexity is cut down to O(|C||U|) + O(|C|2|U/C|), and space complexity to O(|U|). Finally, an example was used to illustrate the effectiveness of the new algorithm.

     

/

返回文章
返回
<th id="5nh9l"></th><strike id="5nh9l"></strike><th id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"></th><strike id="5nh9l"></strike>
<progress id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"><noframes id="5nh9l">
<th id="5nh9l"></th> <strike id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"></span>
<progress id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"><noframes id="5nh9l"><span id="5nh9l"></span><strike id="5nh9l"><noframes id="5nh9l"><strike id="5nh9l"></strike>
<span id="5nh9l"><noframes id="5nh9l">
<span id="5nh9l"><noframes id="5nh9l">
<span id="5nh9l"></span><span id="5nh9l"><video id="5nh9l"></video></span>
<th id="5nh9l"><noframes id="5nh9l"><th id="5nh9l"></th>
<progress id="5nh9l"><noframes id="5nh9l">
259luxu-164