Quiz  /  Machine Learning Gate & PSU MCQ Questions With Answers

  • 1. 
    Artificial Intelligence is the process that allows computers to learn and make decisions like humans

  • True
  • False

  • 2. 
    Because of low bias and high variance , we get _____ model

  • high error
  • perfectly fitting
  • underfitting
  • over fitting

  • 3. 
    This picture shows an application of ...

  • Supervised Learning: Classification
  • Unsupervised Learning: Clustering
  • Unsupervised Learning: Prediction
  • Supervised Learning: Regression

  • 4. 
    ______ is the process of dividing datasets into different categories or groups by adding labels.

  • Regression
  • Clustering
  • Classification
  • K-means

  • 5. 
    Positive examples of the data set are called as _________

  • hypothesis
  • Target concept
  • non members of the concept
  • members of the concept

  • 6. 
    In SVM, non linear problem can be solved by transforming data from _____ dimensional space into _____ dimensional space.

  • high, low
  • low, high
  • low, medium
  • medium, high

  • 7. 
    Which of the following is an example of a deterministic algorithm?

  • K-Means
  • PCA
  • Both of these
  • None of these

  • 8. 
    Suppose there is a basket and it is filled with some fresh fruits. The task is to arrange the same type of fruits at one place. but there is no information about those fruits beforehand, its the first time that the fruits are being seen or discovered. here the example of

  • Reinforcement Learning
  • Supervised Learning
  • Unsupervised Learning
  • None of these

  • 9. 
    KNN Algorithm can be used for

  • Only for Classification
  • Only for Regression
  • Both Classification and Regression
  • None of the Mentioned

  • 10. 
    Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...

  • Unsupervised Learning: Clustering
  • Supervised Learning: Classification
  • Reinforcement Learning
  • Unsupervised Learning: Regression

  • 11. 
    How do you handle missing or corrupted data in a dataset?

  • Drop missing rows or columns
  • Replace missing values with mean/median/mode
  • Assign a unique category to missing values
  • All of the above

  • 12. 
    In__________ decision-making agent that takes actions in an environment and receives reward (or penalty) for its actions in trying to solve a problem

  • Regression
  • classification
  • supervised learning
  • Reinforcement learning

  • 13. 
    A major benefit of an machine with AI is

  • it could do a job too dangerous for a human
  • it could love you like a brother
  • it could chop up your vegetables

  • 14. 
    from confusion matrix,Accuracy is defined as (X)P+N. Then X=?from\ confusion\ matrix,Accuracy\ is\ defined\ as\ \frac{\left(X\right)}{P+N}.\ Then\ X=?from confusion matrix,Accuracy is defined as P+N(X)​. Then X=?

  • TP+PN
  • TP+FP
  • P
  • N

  • 15. 
    ______ is the partition approach of grouping similar datas.

  • KNN
  • K-Means
  • ANN
  • HAC

  • 16. 
    A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college.Which of the following statement is true in following case?

  • Feature F1 is an example of nominal variable.
  • Feature F1 is an example of ordinal variable.
  • It doesn’t belong to any of the above category.
  • Both (a) and (b)

  • 17. 
    The prior goal of unsupervised learning model is to determine the ________ .

  • classification task
  • regression task
  • accuracy of the classified labels
  • data patterns

  • 18. 
    KNN algorithm requires

  • More time for training
  • More time for testing
  • Equal time for training and testing
  • None of the Mentioned

  • 19. 
    Machine Learning has various search/ optimization algorithms, which of the following is not evolutionary computation?

  • Perceptron
  • Genetic Algorithm (GA)
  • Neuro Evolution
  • Genetic Programming (GP)

  • 20. 
    Suitable evaluation metric for measuring the performance of a given regression model is

  • Mean Absolute Error
  • Root Mean Square Error
  • Precision
  • None of these
  • Recall

  • 21. 
    Machine Learning has various function representation, which of the following is not numerical functions?

  • Linear Regression
  • Support Vector Machines
  • Neural Network
  • Case-based

  • 22. 
    __________ has been used to train vehicles to steer correctlyand autonomously on road.

  • Machine learning
  • Data mining
  • Neural networks
  • Robotics

  • 23. 
    What kind of learning algorithm for "Future stock prices or currency exchange rates"?

  • Prediction
  • Recognizing Anomalies
  • Generating Patterns
  • Recognition Patterns

  • 24. 
    You are given reviews of movies marked as positive, negative, and neutral. Classifying reviews of a new movie is an example of

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • None of these

  • 25. 
    What kind of learning algorithm for "Facial identities or facial expressions"?

  • Recognizing Anomalies
  • Prediction
  • Generating Patterns
  • Recognition Patterns

  • 26. 
    In a Decision Tree Leaf Node represents_____________

  • One of the Class Label
  • One of the complete observation
  • One of the attribute
  • None of the Mentioned

  • 27. 
    Targetted marketing, Recommended Systems, and Customer Segmentation are applications in ...

  • Unsupervised Learning: Clustering
  • Supervised Learning: Classification
  • Reinforcement Learning
  • Unsupervised Learning: Regression
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