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1
Q

What type of model is Logistic Regression?

A

B. Classification

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2
Q

What is the target variable type in Logistic Regression?

A

B. Categorical

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3
Q

Which function is commonly used to model probabilities in logistic regression?

A

B. Sigmoid function

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4
Q

What is the main characteristic of binary classification?

A

B. Two classes

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5
Q

What does the log odds in logistic regression represent?

A

B. Odds of one event compared to another

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6
Q

Which metric is used to evaluate how well the logistic regression model predicts labels?

A

A. Sensitivity

B. Specificity

C. Accuracy

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7
Q

What is the equation used for log odds in logistic regression?

A

A. log(P/(1-P))

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8
Q

What does ROC curve represent?

A

B. Trade-off between TPR and FPR

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9
Q

What value represents an ideal AUC (Area Under the Curve) for a perfect model?

A

C. 1

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10
Q

Which library in Python is commonly used for building logistic regression models?

A

C. statsmodels

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11
Q

What does ‘Specificity’ measure in a model?

A

B. True negatives

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12
Q

What is the threshold value optimized using the ROC curve?

A

A. Probability Cutoff

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13
Q

What is an advantage of dummy variable transformation?

A

B. Standardizes scales of variables

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14
Q

What does WOE stand for?

A

A. Weight Of Evidence

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15
Q

What is a key characteristic of WOE transformation?

A

B. Reflects group identity

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16
Q

What does IV (Information Value) indicate?

A

B. Predictive power of variables

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17
Q

Which validation method splits the data into k parts?

A

B. K-fold cross-validation

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18
Q

What does a stable model ensure?

A

C. Performance and variable stability

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19
Q

What is a common issue addressed during sample selection?

A

B. Seasonal fluctuations

20
Q

Which metric measures how many predicted positives are correct?

A

A. Precision

21
Q

What is the formula for odds?

A

A. P/(1-P)

22
Q

Which term represents the trade-off between precision and recall?

A

B. F1-score

23
Q

Why are dummy variables used for categorical data?

A

B. To simplify analysis

24
Q

What does TPR (True Positive Rate) equal?

A

A. Sensitivity

25
What is the main disadvantage of using continuous variables without transformation?
B. Causes model instability
26
What value of IV indicates a variable with weak predictive power?
A. < 0.02
27
What is the purpose of out-time validation?
A. Check model stability over time
28
Which step comes first in building a logistic regression model?
B. Data preparation
29
What does k-fold cross-validation help to avoid?
A. Overfitting | B. Underfitting ## Footnote C. Sampling bias
30
What is the ideal cut-off point derived from?
B. ROC curve
31
Which Python library is used for building logistic regression models?
B. statsmodels
32
What function in the statsmodels library is used for logistic regression?
C. GLM()
33
What is the first step in preparing data for a logistic regression model?
B. Missing value imputation
34
Which Python function can be used to split data into training and testing sets?
A. train_test_split from sklearn.model_selection
35
What method is used to standardize the scales of continuous variables in Python?
A. Min-max scaling B. z-score normalization C. StandardScaler from sklearn.preprocessing
36
What step should be taken if categorical variables are present in the data?
A. Convert them into dummy variables
37
What is the purpose of Recursive Feature Elimination (RFE) in Python?
C. To select important predictors
38
Which Python method is used to evaluate variable importance in logistic regression?
C. Both A and B
39
What Python function is used to compute accuracy, precision, and recall metrics?
A. metrics.classification_report from sklearn
40
What Python module is used for plotting an ROC curve?
B. sklearn.metrics
41
What is the default threshold for classification predictions in logistic regression models?
C. 0.5
42
What Python function from sklearn calculates the AUC?
A. roc_auc_score
43
In Python, which method is used to handle multicollinearity in logistic regression?
A. Variance Inflation Factor (VIF)
44
Which Python command is used to check the coefficients of a logistic regression model?
C. Both A and B
45
How can you plot the confusion matrix in Python?
A. confusion_matrix from sklearn.metrics B. plot_confusion_matrix from sklearn C. seaborn.heatmap for visualization

logistic regression (1 decks)

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