Could you please tell me how a dataset should look like for one class classification. If I have web links, do I need a csv file of link_id and label of a class (for example all links will have a label 0 (target class identifier), because they are considered as positive samples).


closed as unclear what you're asking by Ferdi, cbeleites, Michael Chernick, whuber Mar 16 at 14:51

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  • $\begingroup$ I think it would be helpful to give some more info about your classification problem. What sort of features/variables will you have? Will they be generated from the content of those web links? Is there any way to generate observations from a different class (as binary classification is generally a simpler task)? $\endgroup$ – hamedbh Mar 15 at 16:02
  • $\begingroup$ Thanks for your answer. It will be extraction of words from each link, n_features are words, n_samples are number of links. There is no information about other classes. Can it be outlier detection and in what form I have to represent a dataset. It can be a sort of unsupervised learning. If supervised then how this dataset should be prepared. $\endgroup$ – Migel Mar 16 at 11:33
  • $\begingroup$ I think if you can add this detail to your question you can maybe have it taken off of hold. Worth a try anyway. It sounds like a natural language processing problem maybe, so your decisions would be about how to represent the text data and links. $\endgroup$ – hamedbh Mar 17 at 8:08