Abstract
The problem of ranking a set of objects given some measure of similarity is one of the most basic in machine learning. Recently Agarwal [1] proposed a method based on techniques in semi-supervised learning utilizing the graph Laplacian. In this work we consider a novel application of this technique to ranking binary choice data and apply it specifically to ranking US Senators by their ideology.
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Rwebangira, M. (2012). On Ranking Senators by Their Votes. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25781-0_39
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DOI: https://doi.org/10.1007/978-3-642-25781-0_39
Publisher Name: Springer, Berlin, Heidelberg
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