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When training a neural network to predict housing prices using a dataset that includes latitude and longitude as features, what is the most effective method to account for the physical dependency of location on price?
A
Creating a numeric column from a feature cross of latitude and longitude
B
Providing latitude and longitude as input vectors to the neural net
C
Creating a feature cross of latitude and longitude and bucketizing it at the minute level while using L1 regularization during optimization
D
Creating a feature cross of latitude and longitude and bucketizing it at the minute level while using L2 regularization during optimization
