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Let's say we are using mini-batch gradient descent in tensorflow. Everyday I update last day's model to predict something(regression/classification) by feeding new data to the model. What do I do if a new value for a categorical feature shows up? How do I incorporate it in the existing model?

For example, let's say a feature called state had 3 values till yesterday namely "CA", "IA" and "VA". So the input feature vector in my tensorflow model had three dummy variables- each for one of the three states. Now when I reuse this model today using a new set of data, how do I accomodate for a new value for the feature state, say, for example "NC". How do I change the feature set in the existing model?

arjun
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  • If you actually want your model to fully incorporate this new feature (e.g. use it for the classification task), I don't see how you can achieve this without retraining your model with the new category included. If you want some very limited functionality, please give details for your model and what exactly you are trying to achieve. – iga Aug 23 '17 at 22:52

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