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I have a dataset where I'd like to perform anomaly detection with an Isolation Forest. I don't have any way to validate the model (my data is not labeled - that's why I'm using unsupervised learning) - how can I tell if the model is working all right? I could do a train-test split, but again, how do I know if the predictions are correct if I'm using unlabelled data (plus I'd like to have as many words in my tf-idf vectoriser as possible, but that's another question)? There isn't any data about the amount of contamination either. How should I fine-tune the parameters/validate the results?

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