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logistic regression > Untitled Deck > Flashcards

Untitled Deck Flashcards

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
Q

What is the main disadvantage of using continuous variables without transformation?

A

B. Causes model instability

26
Q

What value of IV indicates a variable with weak predictive power?

A

A. < 0.02

27
Q

What is the purpose of out-time validation?

A

A. Check model stability over time

28
Q

Which step comes first in building a logistic regression model?

A

B. Data preparation

29
Q

What does k-fold cross-validation help to avoid?

A

A. Overfitting

B. Underfitting

C. Sampling bias

30
Q

What is the ideal cut-off point derived from?

A

B. ROC curve

31
Q

Which Python library is used for building logistic regression models?

A

B. statsmodels

32
Q

What function in the statsmodels library is used for logistic regression?

A

C. GLM()

33
Q

What is the first step in preparing data for a logistic regression model?

A

B. Missing value imputation

34
Q

Which Python function can be used to split data into training and testing sets?

A

A. train_test_split from sklearn.model_selection

35
Q

What method is used to standardize the scales of continuous variables in Python?

A

A. Min-max scaling
B. z-score normalization
C. StandardScaler from sklearn.preprocessing

36
Q

What step should be taken if categorical variables are present in the data?

A

A. Convert them into dummy variables

37
Q

What is the purpose of Recursive Feature Elimination (RFE) in Python?

A

C. To select important predictors

38
Q

Which Python method is used to evaluate variable importance in logistic regression?

A

C. Both A and B

39
Q

What Python function is used to compute accuracy, precision, and recall metrics?

A

A. metrics.classification_report from sklearn

40
Q

What Python module is used for plotting an ROC curve?

A

B. sklearn.metrics

41
Q

What is the default threshold for classification predictions in logistic regression models?

A

C. 0.5

42
Q

What Python function from sklearn calculates the AUC?

A

A. roc_auc_score

43
Q

In Python, which method is used to handle multicollinearity in logistic regression?

A

A. Variance Inflation Factor (VIF)

44
Q

Which Python command is used to check the coefficients of a logistic regression model?

A

C. Both A and B

45
Q

How can you plot the confusion matrix in Python?

A

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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