Test Bank
ML4T Machine Learning for Trading
Georgia Tech CS 7646 OMSCS | Questions with
Verified Answers
ML4T (CS7646) Practice Exam –
1. What is the main goal of supervised learning?
A. Find hidden rewards
B. Learn from labeled data
C. Random guessing
D. Data compression
Answer: B
Solution: Supervised learning uses labeled inputs/outputs.
2. What does overfitting mean?
A. Model performs well on training but poorly on test data
B. Model ignores training data
C. Model has no parameters
D. Model is random
Answer: A
Solution: It memorizes instead of generalizing.
,3. What is a feature in machine learning?
A. Output variable
B. Input variable
C. Error term
D. Loss function
Answer: B
Solution: Features are inputs used for prediction.
4. What is reinforcement learning based on?
A. Labels
B. Rewards and penalties
C. Clustering
D. Sorting
Answer: B
5. What is a Q-value?
A. Random number
B. Expected future reward
C. Input feature
D. Dataset size
Answer: B
6. What does a decision tree do?
A. Stores data
B. Splits data based on conditions
C. Removes noise
D. Normalizes data
Answer: B
7. What is regression used for?
A. Classification
B. Continuous prediction
C. Clustering
D. Sorting
Answer: B
, 8. What is classification?
A. Predicting categories
B. Predicting numbers
C. Data cleaning
D. Feature scaling
Answer: A
9. What is a portfolio in trading?
A. Single stock
B. Collection of assets
C. One trade
D. Market index
Answer: B
10. What is diversification?
A. Buying one stock
B. Spreading investments across assets
C. Selling everything
D. Trading daily
Answer: B
11. What is a moving average used for?
A. Random noise
B. Trend smoothing
C. Data deletion
D. Classification
Answer: B
12. What does volatility measure?
A. Price stability
B. Price fluctuation
C. Trading speed
D. Market size
Answer: B
ML4T Machine Learning for Trading
Georgia Tech CS 7646 OMSCS | Questions with
Verified Answers
ML4T (CS7646) Practice Exam –
1. What is the main goal of supervised learning?
A. Find hidden rewards
B. Learn from labeled data
C. Random guessing
D. Data compression
Answer: B
Solution: Supervised learning uses labeled inputs/outputs.
2. What does overfitting mean?
A. Model performs well on training but poorly on test data
B. Model ignores training data
C. Model has no parameters
D. Model is random
Answer: A
Solution: It memorizes instead of generalizing.
,3. What is a feature in machine learning?
A. Output variable
B. Input variable
C. Error term
D. Loss function
Answer: B
Solution: Features are inputs used for prediction.
4. What is reinforcement learning based on?
A. Labels
B. Rewards and penalties
C. Clustering
D. Sorting
Answer: B
5. What is a Q-value?
A. Random number
B. Expected future reward
C. Input feature
D. Dataset size
Answer: B
6. What does a decision tree do?
A. Stores data
B. Splits data based on conditions
C. Removes noise
D. Normalizes data
Answer: B
7. What is regression used for?
A. Classification
B. Continuous prediction
C. Clustering
D. Sorting
Answer: B
, 8. What is classification?
A. Predicting categories
B. Predicting numbers
C. Data cleaning
D. Feature scaling
Answer: A
9. What is a portfolio in trading?
A. Single stock
B. Collection of assets
C. One trade
D. Market index
Answer: B
10. What is diversification?
A. Buying one stock
B. Spreading investments across assets
C. Selling everything
D. Trading daily
Answer: B
11. What is a moving average used for?
A. Random noise
B. Trend smoothing
C. Data deletion
D. Classification
Answer: B
12. What does volatility measure?
A. Price stability
B. Price fluctuation
C. Trading speed
D. Market size
Answer: B
