We present a novel data visualization method based on the extreme learning machine (ELM), which uses the multidimensional scaling (MDS), Pearson correlation and Spearman correlation respectively instead of the common MSE to project the high-dimensional data onto a two-dimensional plane to carry out data visualization. Experimental results show that compared with the recent popular stochastic neighbor embedding (SNE) and t-SNE, the proposed method outperforms them in visual effect and computation performance. Furthermore, these experimental results also show that the MDS-based ELM has the best performance.