SHOGUN provides "static" interfaces to Matlab(tm), R, Python, Octave and provides a command line stand-a-lone executable. The idea behind the static interfaces is to provide a simple environment just enough to do simple experiments. For example, it will allow you to train and evaluate a classifier but not go beyond that. In case you are looking for basically unlimited extensibility (multiple methods like classifiers potentially sharing data and interacting) you might want to look at the Modular Interfaces instead.
In this tutorial we demonstrate how to use shogun to create a simple gaussian kernel based svm classifier:
% LibSVM print LibSVM set_kernel GAUSSIAN REAL 10 1.2 set_features TRAIN ../data/fm_train_real.dat set_labels TRAIN ../data/label_train_twoclass.dat new_svm LIBSVM svm_epsilon 1e-5 svm_use_bias 0 c 0.017 init_kernel TRAIN train_classifier save_classifier libsvm.model load_classifier libsvm.model LIBSVM set_features TEST ../data/fm_test_real.dat init_kernel TEST out.txt = classify