In order to achieve superior performance, various projection space pairs (PSPs) in neighbor embedding (NE) algorithms are introduced aiming to satisfy manifold assumption better. However, the comparison of theses PSPs has not been given much importance in previous researches, which could be a guiding factor for choosing better PSPs before executing the whole neighbor embedding process. Besides, evaluation criterions of final results like Peak Signal to Noise Ratio (PSNR) cannot represent the exact performance of non-linear PSPs due to the non-linear back projection process. To overcome these limitations, we compare different PSPs by introducing an efficient technique using cosine similarity and histogram approach. Experimental results demonstrate the effectiveness of the proposed evaluation method. Moreover, we also identify that non-linear PSPs could obtain superior performance only if the non-linear back projection process is well handled.