Why is logistic regression sensitive to imbalanced datasets?

Because it cannot handle categorical predictors

Because the model may become biased towards the majority class

Because it requires a large sample size

Because it assumes the classes are perfectly separable

A logistic regression model for cancer detection has AUC=0.95 on the training set but AUC=0.60 on the validation set. Which step is most appropriate to address this discrepancy?

Lower the classification threshold to improve validation AUC

Simplify the model by reducing the number of predictors or applying regularization

Use a different random seed and retrain the model

Increase the number of predictors to capture more signal

What does an AUC (Area Under the ROC Curve) of 0.5 indicate about a model's discriminative ability?

The model is biased towards the positive class

The model performs no better than random chance

The model has a high false positive rate

The model has perfect discrimination

In the logistic regression equation, what does the term 'log-odds' (logit) represent?

The odds ratio of the predictor variables

The probability of the positive class

The linear combination of the predictor variables and coefficients

Dell Data Science Foundations

Domain 4Objective 4

Logistic Regression DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 2)

Part of the Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods domain, which accounts for 40% of the DATA-SCIENCE-FOUNDATIONS exam.

25questions here

5free pages

8concepts

40%of the exam

Questions 6–10

6foundation · easy
Why is logistic regression sensitive to imbalanced datasets?
Select an answer first
7expert · hard
A logistic regression model for cancer detection has AUC=0.95 on the training set but AUC=0.60 on the validation set. Which step is most appropriate to address this discrepancy?
Select an answer first
8foundation · easy
What does an AUC (Area Under the ROC Curve) of 0.5 indicate about a model's discriminative ability?
Select an answer first
9expert · medium
A logistic regression model predicts the probability of a customer purchasing a product. The coefficient for 'email opened' is 1.2 (coded 1 if opened, 0 if not). What is the odds ratio for email opened?
Select an answer first
10foundation · easy
In the logistic regression equation, what does the term 'log-odds' (logit) represent?
Select an answer first

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