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arXiv:1709.00379v1 stat. ML 1 Sep 2017Sparse Regularization in Marketing and Economics Guano FengNicholas G. Poison Yuri Wang Jiang EU College of Business Booth School of BusinessDepartment of Statistics
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What is sparse regularization in marketing?
Sparse regularization in marketing is a technique used to prevent overfitting by penalizing the number of non-zero coefficients in a model.
Who is required to file sparse regularization in marketing?
Marketing analysts and data scientists who are working on predictive models in marketing are required to implement sparse regularization.
How to fill out sparse regularization in marketing?
Sparse regularization can be implemented using techniques such as Lasso or Ridge regression during model training.
What is the purpose of sparse regularization in marketing?
The purpose of sparse regularization in marketing is to improve the generalization of predictive models by reducing unnecessary complexity.
What information must be reported on sparse regularization in marketing?
Information such as the type of regularization technique used, the strength of the regularization parameter, and the impact on model performance should be reported.
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