Visualising a Classification in High Dimension

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So far, when discussing classification, we’ve been playing on my toy-dataset (actually, I should no claim it’s mine, it is inspired by the one used in the introduction of Boosting, by Robert Schapire and Yoav Freund). But in ral life, there are more observations, and more explanatory variables.With more than two explanatory variables, it starts to be more complicated to visualise. For instance, consider MYOCARDE=read.table( "http://ift.tt/1Ew09Qc;, head=TRUE,sep=";") where we have observations from people in E.R., for infarctus, and we want to understand who did survive, … Continue reading Visualising a Classification in High Dimension →

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