LeastAngleRegression - Stanford University

Least Angle RegressionBradley Efron, Trevor Hastie, Iain Johnstone and Robert TibshiraniStatistics Department, Stanford UniversityJanuary 9, 2003 AbstractThe purpose of model selection algorithms such asAllSubsets,ForwardSelection,andBackwar dEliminationis to choose a linear model on the basis of the same set ofdata to which the model will be applied. Typically we have available a large collectionof possible covariates from which we hope to select a parsimonious set for the efficientprediction of a response ( LARS ), a new model se-lection algorithm, is a useful and less greedy version of traditional forward selectionmethods.

442 36 1 19.6 71 250 133.2 97 3 4.6 92 57 Table 1. Diabetes study. 442 diabetes patients were measured on 10 baseline variables. A prediction model was desired for the response variable, a measure of disease progression one year after baseline. Tenbaselinevariables,age,sex,bodymassindex,averagebloodpressure,andsixblood

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