I use a logistic regression model for reranking some documents where a normalized features of some candidates may have negative real value so that its predicted value may get lower score(low likelihood for positive class).
I am doing this on Weka within a Java program without using arff file.
Can I use a negative value for a given feature vector? Or should I normalize the dataset so that all negative value be zero?
The reason why I ask this is that I intend to use such a negative valued feature for negative boosting in information retrieval viewpoint. What can be best when I want to embed such negative boosting feature in learning ranking model based on logistic regression.