How about you run 20 vector machines ? Each only identifies how likely one reason is (using distance from separating plane as a "how sure is this SVM" measure).

How about you run 20 vector machines ? Each only identifies how likely one reason is (using distance from separating plane as a "how sure is this SVM" measure). Besides, SVM do not have a particularly good reputation due to the need for good kernels, which requires either massive computing power (just have 10 million kernels) or people with very good domain knowledge. And if you need people with very good domain knowledge, why bother with AI ? AI is hard and people who know both a lot about statistics, AI and programming AND a lot about, say insurance claims, well good look finding them. People with good knowledge about insurance claims and good knowledge of excel, they're, well, not a dime a dozen, but certainly much easier to find.