# Is there a way to add new feature to existing machine learning model and retrain it?

Suppose a machine learning model is trained on two features (f1, f2). If there comes a new feature(f3) is there any way to pass this new feature to existing model and retrain instead of training a model again on the three features?

So the question asks if you can retrain the model after adding another feature.

Answer is yes but you need to instantiate a new model which can accept a 3-feature/dimensional input.

This is due to the mechanics of neural networks whereby in the 1st layer, the features in your original model would be multiplied by a ($$2 x n$$) matrix where $$n$$ represents the number of hidden neurons in the second layer of the model. Therefore by multiplying a ($$3 x 1$$) input with the weight matrix will throw an error.