These m × k similarity values are then used as the meta features, x ′ , and we compute them for training and testing instances.
as a result of this step each instance x is now represented by m tuples of vectors, the first level feature vectors x i 1 , ..., x i |x i | and the newly generated meta feature vectors In our problem of AA, we consider four types of first level features: stylistic features, lexical features, syntactic features, and perplexity values from character 3-gram language models.