Machine Learning & Predictive Analytics Flashcards
7 cards from real DAC practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Machine Learning & Predictive Analytics flashcards as text
What does the bias-variance tradeoff describe?
Answer: The balance between underfitting and overfitting errors
High bias causes underfitting while high variance causes overfitting, and models must balance the two.
Which validation approach is most reliable for a small dataset?
Answer: K-fold cross-validation
K-fold cross-validation uses all data for both training and validation across folds, maximizing reliability on small samples.
A predictive model performs well in testing but degrades over months in production. This is most likely due to what?
Answer: Data drift
Data drift occurs when the statistical properties of incoming data change over time, degrading model performance.
In logistic regression, what does the output represent?
Answer: A probability between 0 and 1
Logistic regression outputs a probability that an observation belongs to the positive class.
Which technique addresses severe class imbalance in a training dataset?
Answer: SMOTE oversampling of the minority class
SMOTE synthesizes new minority-class examples to balance the classes for training.
What is the main advantage of a random forest over a single decision tree?
Answer: It reduces variance by averaging many trees
Averaging predictions across many de-correlated trees reduces variance and improves generalization.
Which metric summarizes model performance across all classification thresholds?
Answer: AUC-ROC
The AUC-ROC measures a classifier's ability to rank positives above negatives across every threshold.