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Question 6 of 4 0 You work for a company that wants to improve spam filtering for mobile email applications. Your data science team gathers
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You work for a company that wants to improve spam filtering for mobile email applications. Your data science team gathers one million messages that have been correctly labeled as spam. You then train an artificial neural network to correctly identify these spam messages. After you train the system, one of the product managers asks why you don't use those same million messages to test the network for accuracy. How should you respond?
If you use the training data, then you're not testing how well the system will do in the future to identify spam.
It is a good idea to use the same messages, but the machine learning system can test its accuracy.
That is an efficient way to train the system without having to find another several million email messages.
An artificial neural network does not use test data like other machine learning systems.
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