A Low Cost Implementation of Multi-label Classification Algorithm Using Mathematica on Raspberry Pi

Abstract Implementation of data mining algorithms with low cost is one of the challenging tasks in the present world of massively increasing data. The key idea of this paper is to utilize the functionalities of Mathematica which is freely accessible on Raspberry Pi for the purpose of implementing Multi-label classification algorithm with low cost. With the facilities available in Mathematica software for Raspberry Pi, the line of code required for implementing data mining algorithms can be reduced sufficiently. Use of Random Kitchen Sink algorithm improves the accuracy of Multi-label classification and brings improvement in terms of memory usage for large dataset.