Figure 3From: Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression dataRandomization accuracies. Support Vector Machine classification accuracies of the Wang et al. breast cancer dataset. The data was randomized a hundred times for fixed target space dimensions two (left) and three (center) and for dimensions estimated by loo-cv (right). In the last case, the plot also shows the results for the original high-dimensional data without reduction. Especially in two and three dimensions, all nonlinear methods are superior to PCA.Back to article page