In the present paper, we propose the efficient algorithm for the parameter reduction of soft sets and we implement it in diagnosing the risk of heart disease problem. Moreover, the efficiency of the algorithm is investigated. The time complexity of the \({\textit{Map}}_-{\textit{Matix}}\) is given by total number of comparisons made to construct \({\textit{map}}_-{\textit{matrix}}\). For n number of objects and f number of attributes, the total number of comparisons is \(n \times f\). Therefore, the time complexity is given O(nf). The algorithm \({\textit{Generate}}_-{\textit{Powerset}}\) takes the total of features f as input and its time complexity is given by \(O(2^f)\). Moreover, the overall efficiency is given by \(O(2^f)\).

在本文中，我们提出了一种有效的算法来减少软集的参数，并将其用于诊断心脏病问题的风险。此外，研究了算法的效率。\（{\ textit {Map}} _- {\ textit {Matix}} \）的时间复杂度由构造\（{\ textit {map}} _- {\ textit {矩阵}} \）。对于n个对象和f个属性，比较的总数为\（n \ times f \）。因此，时间复杂度为O（nf）。算法\（{\ textit {Generate}} _- {\ textit {Powerset}} \）的特征总数为f作为输入，其时间复杂度由\（O（2 ^ f）\）给出。而且，整体效率由\（O（2 ^ f）\）给出。