Feature-Weighted Linear Stacking

3 Nov 2009 Joseph Sill Gabor Takacs Lester Mackey David Lin

Ensemble methods, such as stacking, are designed to boost predictive accuracy by blending the predictions of multiple machine learning models. Recent work has shown that the use of meta-features, additional inputs describing each example in a dataset, can boost the performance of ensemble methods, but the greatest reported gains have come from nonlinear procedures requiring significant tuning and training time... (read more)

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