1. A computer system for classification, comprising: a processor device configured to operate as a text classifier using a plurality of features selected by subspace sampling from a corpus of training data for classification of a document; selecting a subset from the plurality of features by subspace sampling comprises using a probability distribution over a plurality of features from a corpus of training texts, the probability distribution having a probability assigned to each of the plurality of features that is proportional to a square of Euclidean norms of a plurality of rows of a plurality of left singular vectors of a matrix of the plurality of features representing the corpus of training texts; and a storage operably coupled to the text classifier for storing a plurality of texts classified using the plurality of features selected by subspace sampling into a plurality of classes.