Another view on reduction of parameters in soft sets

The basic aim of this paper is to discuss the idea of reduction of parameters in case of soft sets. It is studied that there is an approximation space of Pawlak associated with a soft set. A very simple technique is developed here to materialize the notion reduction of parameters.

Deletion of condition parameters in a soft set in such a way that classification by decision parameter remains the same. Figure optionsDownload as PowerPoint slideHighlights
► A soft set can be presented as an information system.
► A soft equivalence relation gives rise to a classical information system which generates an approximation space in Pawlak sense.
► It is studied that how we can reduce the number of condition parameters for a soft set to the minimum without distorting its original classification ability of the soft set.
► The method of reduction of parameters proposed here is very much similar to reduction of attributes in case of rough sets.
► In this paper instead of a subset of parameters as a whole, parameters are reduced one by one. This makes it more efficient in case of large data.