jDRCluster is a Java-based tool for the dimension reduction techniques and cluster analysis. The methods include singular value decomposition (SVD), principle components analysis (PCA), sliced inverse regression (SIR), sliced average variance estimation (SAVE), principal Hessian direction (phd), multidimensional scaling (MDS) and ISOMAP. The output can be saved and plotted on the 2D or 3D scatterplots. The most important feature of the jDRCluster in the future will be the linking among graphics produced by different dimension reduction methods. [Ongoing Work]

Current version: v0.1 build 20070520.
History: 2004/06~2007/05: JDRViewer; 2007/05~present: jDRCluster