Machine Learning Questions

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17 Apr 2025 03:18 PM study24x7

What is the main challenge with algorithmic decision-making in sensitive domains like healthcare and law enforcement?

A

Improving accuracy

B

Ensuring fairness and accountability

C

Reducing data size

D

Minimizing computational cost

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Machine Learning Questions

5 followers study24x7

17 Apr 2025 03:18 PM study24x7

Why is transparency important in machine learning models?

A

To improve model accuracy

B

To ensure data security

C

To explain model decisions

D

To reduce model complexity

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Machine Learning Questions

5 followers study24x7

17 Apr 2025 03:17 PM study24x7

What does bias in machine learning models refer to?

A

The model’s performance

B

Prejudice in data or decisions

C

Incorrect features

D

Inefficient algorithms

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Machine Learning Questions

5 followers study24x7

16 Apr 2025 11:09 AM study24x7

What is a primary ethical concern in machine learning?

A

Data storage

B

Model accuracy

C

Bias and fairness

D

Feature selection

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Machine Learning Questions

5 followers study24x7

16 Apr 2025 11:09 AM study24x7

A reinforcement learning model is slow to converge. What could speed up the training process?

A

Use a smaller dataset

B

Decrease the discount factor

C

Increase the learning rate

D

Increase the number of actions

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Machine Learning Questions

5 followers study24x7

16 Apr 2025 11:04 AM study24x7

An agent in a reinforcement learning model is not exploring enough. What could help resolve this?

A

Decrease the learning rate

B

Increase the exploration rate (epsilon)

C

Decrease the reward function

D

Increase the discount factor

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Machine Learning Questions

5 followers study24x7

16 Apr 2025 10:49 AM study24x7

How do you update the Q-value in the Q-learning algorithm?

A

By maximizing the reward

B

By using the Bellman equation

C

By minimizing error

D

By using a classifier

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Machine Learning Questions

5 followers study24x7

15 Apr 2025 11:14 AM study24x7

Which algorithm in reinforcement learning is used to optimize the action-value function?

A

Q-Learning

B

Random Forest

C

Support Vector Machine

D

Gradient Boosting

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Machine Learning Questions

5 followers study24x7

15 Apr 2025 11:13 AM study24x7

Which Python library is commonly used to implement reinforcement learning algorithms?

A

keras

B

scikit-learn

C

gym

D

numpy

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Machine Learning Questions

5 followers study24x7

15 Apr 2025 11:13 AM study24x7

What is the trade-off between exploration and exploitation in reinforcement learning?

A

Exploring only actions that maximize reward

B

Exploring new actions

C

Balancing between trying new actions and maximizing known rewards

D

Ignoring all rewards

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Machine Learning Questions

5 followers study24x7

14 Apr 2025 11:42 AM study24x7

What is the role of the agent in reinforcement learning?

A

To gather data

B

To provide rewards

C

To take actions based on policy

D

To process the environment data

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Machine Learning Questions

5 followers study24x7

14 Apr 2025 11:40 AM study24x7

What is the goal of reinforcement learning?

A

To predict continuous values

B

To minimize error rate

C

To maximize cumulative reward

D

To classify data points

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Machine Learning Questions

5 followers study24x7

14 Apr 2025 11:35 AM study24x7

A Random Forest model is overfitting on the training data. What could resolve this?

A

Increase the number of estimators

B

Reduce the number of features

C

Increase the max_depth parameter

D

Reduce the number of trees

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Machine Learning Questions

5 followers study24x7

11 Apr 2025 01:01 PM study24x7

How do you implement AdaBoost in Python using sklearn?

A

BoostingAda()

B

AdaBoostClassifier()

C

BoostAda()

D

Adaboost()

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Machine Learning Questions

5 followers study24x7

11 Apr 2025 01:00 PM study24x7

Which function in sklearn is used to implement a Random Forest classifier?

A

RandomForestClassifier()

B

ForestClassifier()

C

RandomForest()

D

ForestRandom()

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Machine Learning Questions

5 followers study24x7

11 Apr 2025 01:00 PM study24x7

What is the role of weak learners in boosting?

A

To make accurate predictions

B

To identify outliers

C

To correct mistakes from previous learners

D

To increase bias

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Machine Learning Questions

5 followers study24x7

10 Apr 2025 12:36 PM study24x7

What is the key difference between bagging and boosting in ensemble learning?

A

Bagging focuses on reducing bias

B

Boosting focuses on reducing variance

C

Bagging trains models in parallel

D

Boosting uses a single model

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Machine Learning Questions

5 followers study24x7

10 Apr 2025 12:35 PM study24x7

What is the main advantage of ensemble learning?

A

Reduces the number of features

B

Increases model complexity

C

Improves model performance by combining multiple models

D

Increases training time

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Machine Learning Questions

5 followers study24x7

10 Apr 2025 12:34 PM study24x7

An SVM model is overfitting on the training data. What should be adjusted to mitigate this?

A

Increase the value of C

B

Decrease the value of C

C

Increase the kernel size

D

Use a larger dataset

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Machine Learning Questions

5 followers study24x7

09 Apr 2025 11:23 AM study24x7

An SVM model performs poorly on a dataset with overlapping classes. What could improve its performance?

A

Increase the regularization parameter (C)

B

Use a linear kernel

C

Use a non-linear kernel

D

Reduce the number of support vectors

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