PROFESSIONAL-DATA-ENGINEER · Question #172
You're training a model to predict housing prices based on an available dataset with real estate properties. Your plan is to train a fully connected neural net, and you've discovered that the…
The correct answer is C. Create a feature cross of latitude and longitude, bucketize at the minute level and use L1 regularization during optimization. Explanation/Reference: Use L1 regularization when you need to assign greater importance to more influential features. It shrinks less important feature to 0. L2 regularization performs better when all input features influence the output & all with the weights are of equal size.
Question
Options
- AProvide latitude and longitude as input vectors to your neural net.
- BCreate a numeric column from a feature cross of latitude and longitude.
- CCreate a feature cross of latitude and longitude, bucketize at the minute level and use L1 regularization during optimization.
- DCreate a feature cross of latitude and longitude, bucketize it at the minute level and use L2 regularization during optimization.
How the community answered
(36 responses)- A31% (11)
- B8% (3)
- C44% (16)
- D17% (6)
Explanation
Explanation/Reference: Use L1 regularization when you need to assign greater importance to more influential features. It shrinks less important feature to 0. L2 regularization performs better when all input features influence the output & all with the weights are of equal size.
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