Muon scattering tomography is believed to be a promising technique for cargo container inspection, owing to the ability of natural muons to penetrate into dense materials and the absence of artificial radiation. In this work, the material discrimination ability of muon scatter-ing tomography is evaluated based on experiments at the Tsinghua University cosmic ray muon tomography facility, with four materials: flour (as drugs substitute), aluminum, steel, and lead. The features of the different materials could be discriminated with cluster analysis and classifiers based on support vector machine. The overall discrimination precisions for these four materials could reach 70, 95, and 99% with 1-, 5-, and 10-min-long measurement, respectively.