Prior to consulting with your team, the analytics group at Greyson created a model to predict which customers are most likely to renew using linear regression with the LASSO shrinkage method. | This is incorrect. They should be using a classification model for this problem. This is correct because LASSO can help prevent overfitting with large numbers of predictor variables. This is in incorrect. With a large number of observations, they should use PCA for regression first and then fit the model to increase prediction accuracy.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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**Question:**

Prior to consulting with your team, the analytics group at Greyson created a model to predict which customers are most likely to renew using linear regression with the LASSO shrinkage method.

- [X] This is incorrect. They should be using a classification model for this problem.
- [ ] This is correct because LASSO can help prevent overfitting with large numbers of predictor variables.
- [ ] This is incorrect. With a large number of observations, they should use PCA for regression first and then fit the model to increase prediction accuracy.

In this example, the correct answer is marked as:
- This is incorrect. They should be using a classification model for this problem.

The linear regression with LASSO shrinkage method may not be appropriate for predicting whether customers will renew, as this typically is a classification problem rather than a regression problem. Classification models are better suited for predicting categorical outcomes.
Transcribed Image Text:**Question:** Prior to consulting with your team, the analytics group at Greyson created a model to predict which customers are most likely to renew using linear regression with the LASSO shrinkage method. - [X] This is incorrect. They should be using a classification model for this problem. - [ ] This is correct because LASSO can help prevent overfitting with large numbers of predictor variables. - [ ] This is incorrect. With a large number of observations, they should use PCA for regression first and then fit the model to increase prediction accuracy. In this example, the correct answer is marked as: - This is incorrect. They should be using a classification model for this problem. The linear regression with LASSO shrinkage method may not be appropriate for predicting whether customers will renew, as this typically is a classification problem rather than a regression problem. Classification models are better suited for predicting categorical outcomes.
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