CHOOSE THE CORRECT ANSWER, NO FURTHER EXPLANATION IS NEEDED

CHOOSE THE CORRECT ANSWER, NO FURTHER EXPLANATION IS NEEDED 1…. CHOOSE THE CORRECT ANSWER, NO FURTHER EXPLANATION IS NEEDED  1. Which of the following learning problems are supervised learning problems? (multiple answers) A)RegressionB)ClusteringC)Classification  2. Which of the following learning problems are unsupervised learning problems?  (multiple answers) A)ClusteringB)Dimensionality ReductionC)Prediction 3. Which of the following learning problems are reinforcement learning problems?  A)Association rulesB)Sequential decision makingC)Feature extraction 4. In which cases is supervised learning useful?  (multiple answers) A)Problems where there is no target variableB)Problems where each user needs a custom functionC)Problems where the desired function changes frequently 5. Which are the three main components of a supervised learning problem?A)State / Action / RewardB)Evaluation / Representation / OptimizationC)Evaluation / Metric / Number of samples 6. By increasing the size of the hypothesis space we increase the risk of:A)OverfittingB)Underfitting 7. Which of the following are parametric methods?  (multiple answers) A)Linear regressionB)Decision treesC)Artificial neural networks 8. How can we contrast overfitting in linear regression? (multiple answers) A)Decreasing the number of featuresB)RegularizationC)Increasing the number of features 9. Which method is used for optimizing the parameters of an artificial neural network?A)Closed-formB)Stochastic gradientC)Brute force 10. A dataset can be split intoA)Train / Validation / TestB)Train / Evaluation / OptimizationC)Supervised / Unsupervised 11. Which of the following are classes of model selection techniques?  (multiple answers) A)Resampling methodsB)RegularizationC)Probabilistic measures 12. What is the main drawback of the cross-validation technique?A)Requires many samplesB)Computational complexityC)High memory requirements 13. In K-means the number of clusters is automatically identified.TrueFalse 14. In which of the following tasks can clustering be used?  (multiple answers) A)Reducing overfittingB)Anomaly detectionC)Improving supervised learning models 15. How can clustering be used for improving supervised learning?A)Tuning the hyperparametersB)Training a different model for each clusterC)Reducing the number of parameters 16. What is the curse of dimensionality?A)It is related to the difficulties with learning in a high-dimensional feature spaceB)It is the exponential increase in the computational times as the number of samples growsC)It is related to the problem of underfitting 17. PCA produces new features that are linear combinations of the original ones.TrueFalse  18. Autoencoders are composed of:A)Train / Validation / TestB)Encoder / Bottleneck / DecoderC)Eigenvectors / Eigenvalues 19. In the Apriori algorithm, what is the minimum support threshold?A)The minimum number of subsets of items to be consideredB)The minimum number of items inside a subsetC)The minimum number of occurrences to consider a subset of items as frequent 20. What is implied by the anti-monotone property?A)All subsets of a frequent itemset must be frequentB)If an itemset is frequent, all its supersets will be frequentC)All subsets of an infrequent itemset must be infrequent 21. What is the confidence of a rule?A)How more often two groups of items occur together than expected, if they were independent to each otherB)How often one or more items go into a basket when other items are already thereC)How often we can find items together in the same basket 22. The goal of a reinforcement-learning agent is to maximize the immediate reward.TrueFalse 23. The Rubik’s cube game is a sequential decision-making problem withA)Finite states, finite actions, and it is partially observableB)Finite states, finite actions, and it is fully observableC)Finite states, continuous actions, and it is partially observable 24. The Poker game is a sequential decision-making problem withA)Deterministic transitions, partial observable state, multiple agentsB)Stochastic transitions, fully observable state, single agentC)Stochastic transitions, partial observable state, multiple agents 25. The Markov assumption states thatA)the past is independent of the past given the futureB)the future is independent of the past given the presentC)the present is independent of the future given the past 26. Can the Bellman expectation equation be solved in closed-form?NoYes   27. Value Iteration and Policy Iteration algorithms can be used even when the state transition model is unknownFalseTrue  28. An experience sample is composed ofA)State, action, discount factor, rewardB)State, action, next state, rewardC)State, action, next state, next action 29. Q-learning is a value-based methodTrueFalse 30. Which kind of approaches are more suited for continuous action problems?  (multiple answers) A)Policy-based methodsB)Value-based methodsC)Actor-critic methods Engineering & Technology Computer Science INGENIRIA 324

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