Robust Classification for Imprecise Environments

In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. In some cases, the performance of the hybrid actually can surpass that of the best known classifier. This robust performance extends across a wide variety of comparison frameworks, including the optimization of metrics such as accuracy, expected cost, lift, precision, recall, and workforce utilization. The hybrid also is efficient to build, to store, and to update. The hybrid is based on a method for the comparison of classifier performance that is robust to imprecise class distributions and misclassification costs. The ROC convex hull (ROCCH) method combines techniques from ROC analysis, decision analysis and computational geometry, and adapts them to the particulars of analyzing learned classifiers. The method is efficient and incremental, minimizes the management of classifier performance data, and allows for clear visual comparisons and sensitivity analyses. Finally, we point to empirical evidence that a robust hybrid classifier indeed is needed for many real-world problems.Comment: 24 pages, 12 figures. To be published in Machine Learning Journal. For related papers, see http://www.hpl.hp.com/personal/Tom_Fawcett/ROCCH

A signed ee-expansion of the chromatic symmetric function and some new ee-positive graphs

We prove a new signed elementary symmetric function expansion of the chromatic symmetric function of any unit interval graph. We then use sign-reversing involutions to prove new combinatorial formulas for many families of graphs, including the K-chains studied by Gebhard and Sagan, formed by joining cliques at single vertices, and for graphs obtained from them by removing any number of edges from any of the cut vertices. We also introduce a version for the quasisymmetric refinement of Shareshian and Wachs.Comment: 73 pages, 24 figure

American Culture Through Amish Eyes: Perspectives of an Anarchist Protest Movement

America's Old Order Amish have managed to avoid some of the most serious social problems facing the larger sociery. This paper identifies the countercrlltural and anarchistic elements ofAmish society and outlines its resemblance to sodalmovements and to other separationist/pacifist societies ofthe past. .Also explored are Amish attitudes toward materialism, technology, art, deviant behavior and non-violent resistance and how these attitudes shape internal sodaI behaviors as weD as interactions with outsiders. Finally, brief consideration "is given to the question of how the study of the Amish might inform students of the larger culture and other interested outsiders

Major Malfunction: Racial and Ethnic Disparities in What Students Study

This analysis explores bachelor's degrees earned by race and ethnicity, broken down by area of study. The report identifies the majors and programs that produce the highest and lowest median incomes (both at the start of one's career and in the middle of one's career) and probes for uneven distributions of African American and Latino students. The report finds that these students disproportionately earn more degrees in low-paying majors, and fewer degrees in the highest paying majors