Retraining a machine learning model Created a Machine Learning model on some data. Used this model for predicting test data. Model has learnt only from training data. How this model can be retrained as new data come in for prediction. I don't know whether it is true that retraining a model is necessary so that it can predict new data more accurately.
It depends on a lot of factors:


Does the function you're learning change overtime ? If you try to detect dogs in pictures, and you already have a good accuracy, then relearning is not necessary. But if you try to detect topics in news streams, then you'll need to update your model regularly. 
Do you have initially enough data ? If you receive a stream of training data, then you should find an algorithm that can be trained in an online manner. 
If you are looking for constantly improving the accuracy, then the more data you feed the better results you'll get. Regularly retraining a new model with the old data + the new ones might be sufficient.