We introduce a dimension adaptive sparse grid combination tech- nique for the machine learning problems of classification and regres- sion. A function over a d-dimensional space, which assumedly de- scribes the relationship between the features and the response vari- able, is reconstructed using a linear combination of partial functions that possibly depend only on a subset of all features. The partial functions are adaptively chosen during the computational procedure. This approach...[Show more]
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