I would like to have an invalid category in my SVM classification. For example considering fruit classification, I want to have APPLE, ORANGE, BANANA and 'NOT FRUIT' (invalid). I was wondering if it's better to create a binary SVM classifier for each category (one for APPLE one for ORANGE, etc) or create a SVM classifier with the invalid category as one of the classes and feed it with invalid training data.
To be a bit more specific, I have a classifier that categorizes time series data. I need to classify some of the fed time series to invalid categories (or basically non of the desired categories).