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I am working with a text classification system. Here, my data-set has around 30 intents. But the problem is I have no system developed to handle inputs that don't go under any of the intents. So, in this case, I am going to train a One class classification model. To teach it how normal data looks, I am going to merge all my training data (of all intents) and train with them. Which feature-extraction and algorithm combo will be best suited for these kinds of tasks? Is there any trade-off, best practice, or other information to know?

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