My goal is to find out where a user would cut a curve. During training, whenever a point on a curve is chosen by the user to be a cutting point, we record some features and use the label '+1' to indicate these features correspond to a cutting point. In order to reduce the training efforts, we would like to avoid recording the points where the user would not cut.
In other words, our training data only consists of inputs labeled with '+1'. I would like to know if there's any SVM-related technique which can handle this case. Finally, we would like the learning machine to tell us whether a point is a cutting point or not.