Machine Learning MCQ

Machine Learning MCQ

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  • 17th Mar, 2023

Machine Learning MCQ Questions

Machine learning is a field of computer science that deals with the problem of finding mathematical and statistical functions that best explain the relationship between input data, output data, and other inputs (external) to a system. Machine learning has some uses in areas such as detection, recommendation systems, fraud detection, machine translation, visual recognition, and the development of autonomous robotic systems.

Finally, Take the Machine Learning MCQ Test and identify your strengths in machine learning. It will help you to understand the ML concepts well & improve your knowledge.

Machine Learning MCQ with Answers

1) What is machine learning?

  • A. The selective acquisition of knowledge through the use of manual programs
  • B.The selective acquisition of knowledge through the use of computer programs
  • C.The autonomous acquisition of knowledge through the use of manual programs
  • D.The autonomous acquisition of knowledge through the use of computer programs

2) Machine Learning is a field of AI consisting of learning algorithms that ..............

  • A. At executing some task
  • B.Over time with experience
  • C.Improve their performance
  • D.All of the above

3) .............. is a widely used and effective machine learning algorithm based on the idea of bagging.

  • A. Regression
  • B.Classification
  • C.Decision Tree
  • D.Random Forest

4) What is the disadvantage of decision trees?

  • A. Factor analysis
  • B.Decision trees are robust to outliers
  • C.Decision trees are prone to be overfit
  • D.All of the above

5) How can you handle missing or corrupted data in a dataset?

  • A. Drop missing rows or columns
  • B.Assign a unique category to missing values
  • C.Replace missing values with mean/median/mode
  • D.All of the above
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6) Which of the followings are most widely used metrics and tools to assess a classification model?

  • A. Confusion matrix
  • B.Cost-sensitive accuracy
  • C.Area under the ROC curve
  • D.All of the above

7) Machine learning algorithms build a model based on sample data, known as .................

  • A. Training Data
  • B.Transfer Data
  • C.Data Training
  • D.None of the above

8) Machine learning is a subset of ................

  • A. Deep Learning
  • B.Artificial Intelligence
  • C.Data Learining
  • D.None of the above

9) A Machine Learning technique that helps in detecting the outliers in data.

  • A. Clustering
  • B.Classification
  • C.Anamoly Detection
  • D.All of the above

10) Who is the father of Machine Learning?

  • A. Geoffrey Hill
  • B.Geoffrey Chaucer
  • C.Geoffrey Everest Hinton
  • D.None of the above

11) What is the most significant phase in a genetic algorithm?

  • A. Selection
  • B.Mutation
  • C.Crossover
  • D.Fitness function

12) Which one in the following is not Machine Learning disciplines?

  • A. Physics
  • B.Information Theory
  • C.Neurostatistics
  • D.Optimization Control

13) Machine Learning has various function representation, which of the following is not function of symbolic?

  • A. Decision Trees
  • B.Rules in propotional Logic
  • C.Rules in first-order predicate logic
  • D.Hidden-Markov Models (HMM)

14) ................... algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.

  • A. Deep Learning
  • B.Machine Learning
  • C.Artificial Intelligence
  • D.None of the above

15) What are the three types of Machine Learning?

  • A. Supervised Learning
  • B.Unsupervised Learning
  • C.Reinforcement Learning
  • D.All of the above

16) Which of the following is not a supervised learning?

  • A. PCA
  • B.Naive Bayesian
  • C.Linear Regression
  • D.Decision Tree Answer

17) Real-Time decisions, Game AI, Learning Tasks, Skill acquisition, and Robot Navigation are applications of .............

  • A. Reinforcement Learning
  • B.Supervised Learning: Classification
  • C.Unsupervised Learning: Regression
  • D.None of the above

18) Which of the following is not numerical functions in the various function representation of Machine Learning?

  • A. Case-based
  • B.Neural Network
  • C.Linear Regression
  • D.Support Vector Machines

19) Common classes of problems in machine learning is ..............

  • A. Clustering
  • B.Regression
  • C.Classification
  • D.All of the above

20) Which of the folloiwng clustering algorithm merges and splits nodes to help modify nonoptimal partitions?

  • A. K-Means clustering
  • B.Conceptual clustering
  • C.Agglomerative clustering
  • D.All of the above

21) Missing data items are ........................ with Bayes classifier.

  • A. Ignored
  • B.Treated as equal compares
  • C.Treated as unequal compares.
  • D.Replaced with a default value.

22) Which supervised learning technique can process both numeric and categorical input attributes?

  • A. Bayes classifier
  • B.Linear regression
  • C.Ogistic regression
  • D.None of the above

23) Logistic regression is a ........... regression technique that is used to model data having a ............ outcome.

  • A. Linear, binary
  • B.Linear, numeric
  • C.Nonlinear, binary
  • D.Nonlinear, numeric

24) Regression trees are often used to model which data?

  • A. Linear
  • B.Nonlinear
  • C.Categorical
  • D.None of the above

25) What is called the average squared difference between classifier predicted output and actual output?

  • A. Mean relative error
  • B.Mean squared error
  • C.Mean absolute error
  • D.Root mean squared error

26) Data used to optimize the parameter settings of a supervised learner model is called ...............

  • A. Test
  • B.Training
  • C.Validation
  • D.None of the above

27) Bootstrapping allows us to choose the same training instance several times.

  • A. True
  • B.False

28) The average positive difference between computed and desired outcome values

  • A. Mean positive error
  • B.Mean absolute error
  • C.Mean squared error
  • D.Root mean squared error

29) Which of the following statement is true about prediction problems?

  • A. The output attribute must be numeric.
  • B.The output attribute must be categorical
  • C.The resultant model is designed to determine future outcomes
  • D.The resultant model is designed to classify current behavior.

30) What is the another name for an output attribute?

  • A. Predictive variable
  • B.Estimated variable
  • C.Dependent variable
  • D.Independent variable

31) Supervised learning and unsupervised clustering both require at least one .............

  • A. Input attribute
  • B.Output attribute
  • C.Hidden attribute
  • D.Categorical attribute

32) ............ is not a machine learning algorithm.

  • A. SVG
  • B.SVM
  • C.Random forest
  • D.All of the above

33) Identify which is not machine learning disciplines?

  • A. Physiscs
  • B.Information theory
  • C.Nuero Statistics
  • D.None of the above

34) What is the full form of PAC?

  • A. Probably Approx Cost
  • B.Probably Approximate Correct
  • C.Probability Approx Communication
  • D.None of the above

35) Analysis of Machine Learning algorithm needs ................

  • A. Statistical learning theory
  • B.Computational learning theory
  • C.Both Statistical & Computational learning theory
  • D.None of the above

36) Choose the incorrect numerical functions in the various function representation of machine learning.

  • A. Case-based
  • B.Neural Network
  • C.Linear regression
  • D.All of true

37) What are successful applications of Machine Learning?

  • A. Learning to recognize spoken words
  • B.Learning to drive an autonomous vehicle
  • C.Learning to classify new astronomical structures
  • D.All of the above

38) What is called the application of machine learning methods to large databases?

  • A. Data mining
  • B.Internet of things
  • C.Artificial intelligence
  • D.None of the above

39) If machine learning model output involves target variable then that model is called as predictive model.

  • A. True
  • B.False

40) ............ are the best machine learning method.

  • A. Fast
  • B.Accuracy
  • C.Scalable
  • D.All of the above

41) What is the output of training process in machine learning?

  • A. Null
  • B.Accuracy
  • C.Machine learning model
  • D.Machine learning algorithm

42) A model of language consists of the categories, does not include .................

  • A. Language units
  • B.Structural units
  • C.System constraints
  • D.Role structure of units

43) Regression discovers causal relationships.

  • A. True
  • B.False

44) ............. is the approach of basic algorithm for decision tree induction.

  • A. Greedy
  • B.Top Down
  • C.Procedural
  • D.Step by Step

45) What is the way to ensemble multiple classifications or regression?

  • A. Bagging
  • B.Blending
  • C.Boosting
  • D.Stacking

46) What is the most common issue when using Machine Learning?

  • A. Poor Data Quality
  • B.Lack of skilled resources
  • C.Inadequate Infrastructure
  • D.None of the above

47) In Machine learning the module that must solve the given performance task is known as ...............

  • A. Critic
  • B.Generalizer
  • C.Performance system
  • D.All of these

48) Which methods are used for the calibration in Supervised Learning?

  • A. Platt Calibration
  • B.Isotonic Regression
  • C.Both Platt Calibration & Isotonic Regression
  • D.None of the above

49) How many types are available in machine learning?

  • A. 2
  • B.3
  • C.4
  • D.5

50) The Bayes rule can be used in ................

  • A. Solving queries
  • B.Increasing complexity
  • C.Decreasing complexity
  • D.Answering probabilistic query

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