In　this　letter,　a　novel　weighted　mean　square　error　(WMSE)　is　proposed　to　improve　the　DNN-based　mask　approximation　method　for　speech　enhancement,　in　which　the　weighting　is　closely　related　to　the　power　exponent　about　noisy　spectrum　amplitude　(NSA)　base.　The　power　exponents　0　and　2　separately　reflect　ideal　amplitude　masking　(IAM)　without　any　clippings　and　the　indirect　mapping　(IM)　on　short-time　spectral　amplitude　(STSA),　and　it　is　highly　related　to　the　enhanced　spectrum　and　the　performance　of　the　enhanced　signal　based　on　the　tests.　Also,　the　experimental　results　show　that　the　outstanding　weighting　is　the　noisy　spectrum　base　with　the　power　exponent　1　for　the　phase-unaware　masking　and　results　in　better　harmonic　structure　restoration.　The　objective　function　with　the　WMSE　on　the　NSA　(WMSE-NSA)　can　averagely　improve　0.1　on　the　test　of　perceptual　evaluation　of　speech　quality　(PESQ)　and　1.7%　on　the　test　of　short-time　objective　intelligibility　(STOI)　compared　with　the　MSE-based　mask　approximation　methods.