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Because of the way in which SVR does its classification, hyperplane separation in a transformed version of the vector space, it is impossible to determine which features do the most work. The tokenizer counts on clear markers for these, e.
The authors apply logistic and linear regression on counts of token unigrams occurring at least 10 times in their corpus. For SVR and LP, these are rather varied, but TiMBL s confidence value consists of the proportion of selected class cases among the nearest neighbours, which with k at 5 is practically always 0. We see the women focusing on personal matters, leading to important content words like love and boyfriend, and important style words like I and other personal pronouns.
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