Exhaustive search for sparse variable selection in linear regression

7 Jul 2017Yasuhiko IgarashiHikaru TakenakaYoshinori Nakanishi-OhnoMakoto UemuraShiro IkedaMasato Okada

We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse... (read more)

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