Machine Learning MCQ with Answers

  1. What is machine learning?
  2. Machine Learning is a field of AI consisting of learning algorithms that ..............
  3. .............. is a widely used and effective machine learning algorithm based on the idea of bagging.
  4. What is the disadvantage of decision trees?
  5. ................. is a widely used and effective machine learning algorithm based on the idea of bagging.
  6. How can you handle missing or corrupted data in a dataset?
  7. Which of the followings are most widely used metrics and tools to assess a classification model?
  8. Machine learning algorithms build a model based on sample data, known as .................
  9. Machine learning is a subset of ................
  10. A Machine Learning technique that helps in detecting the outliers in data.
  11. Who is the father of Machine Learning?
  12. What is the most significant phase in a genetic algorithm?
  13. Which one in the following is not Machine Learning disciplines?
  14. Machine Learning has various function representation, which of the following is not function of symbolic?
Machine Learning MCQ

Take Machine Learning MCQ Quiz & Online Test to Test your Knowledge

We have listed below the best Machine Learning MCQ Questions, that checks your basic knowledge of Machine Learning. This Machine Learning MCQ Test contains 20 multiple-choice questions. You have to select the right answer to every question to check your final preparation. apart from this, You can also download below the Machine Learning MCQ Pdf completely free.

  • The selective acquisition of knowledge through the use of manual programs
  • The selective acquisition of knowledge through the use of computer programs
  • The autonomous acquisition of knowledge through the use of manual programs
  • The autonomous acquisition of knowledge through the use of computer programs
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  • At executing some task
  • Over time with experience
  • Improve their performance
  • All of the above
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  • Factor analysis
  • Decision trees are robust to outliers
  • Decision trees are prone to be overfit
  • All of the above
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  • Drop missing rows or columns
  • Assign a unique category to missing values
  • Replace missing values with mean/median/mode
  • All of the above
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  • Confusion matrix
  • Cost-sensitive accuracy
  • Area under the ROC curve
  • All of the above
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  • Training Data
  • Transfer Data
  • Data Training
  • None of the above
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  • Deep Learning
  • Artificial Intelligence
  • Data Learining
  • None of the above
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  • Clustering
  • Classification
  • Anamoly Detection
  • All of the above
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  • Geoffrey Hill
  • Geoffrey Chaucer
  • Geoffrey Everest Hinton
  • None of the above
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  • Selection
  • Mutation
  • Crossover
  • Fitness function
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  • Physics
  • Information Theory
  • Neurostatistics
  • Optimization Control
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  • Decision Trees
  • Rules in propotional Logic
  • Rules in first-order predicate logic
  • Hidden-Markov Models (HMM)
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  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • All of the above
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  • PCA
  • Naive Bayesian
  • Linear Regression
  • Decision Tree Answer
  • Reinforcement Learning
  • Supervised Learning: Classification
  • Unsupervised Learning: Regression
  • None of the above
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  • Clustering
  • Regression
  • Classification
  • All of the above
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