Data-dependent cost-sensitive training In our baseline approach, we use the standard perceptron training.
whenever the algorithm sees a training instance x i with its corresponding label y i , it updates the weight vector θ for iteration t based on the difference between the feature vector φ(x i , y i ) of the gold label and the feature vector In Eq.