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This set of Machine Learning (ML) Multiple Choice Questions & Answers (MCQs) focuses on Machine Learning Set 25

Q1 | For a multiple regression model, SST = 200 and SSE = 50. The multiple coefficient ofdetermination is
Q2 | A nearest neighbor approach is best used
Q3 | Another name for an output attribute.
Q4 | Classification problems are distinguished from estimation problems in that
Q5 | Which statement is true about prediction problems?
Q6 | Which of the following is a common use of unsupervised clustering?
Q7 | The average positive difference between computed and desired outcome values.
Q8 | Selecting data so as to assure that each class is properly represented in both the training andtest set.
Q9 | The standard error is defined as the square root of this computation.
Q10 | Data used to optimize the parameter settings of a supervised learner model.
Q11 | Bootstrapping allows us to
Q12 | The correlation coefficient for two real-valued attributes is –0.85. What does this value tell you?
Q13 | The average squared difference between classifier predicted output and actual output.
Q14 | Simple regression assumes a __________ relationship between the input attribute and outputattribute.
Q15 | Regression trees are often used to model _______ data.
Q16 | The leaf nodes of a model tree are
Q17 | Logistic regression is a ________ regression technique that is used to model data having a_____outcome.
Q18 | This technique associates a conditional probability value with each data instance.
Q19 | This supervised learning technique can process both numeric and categorical input attributes.
Q20 | With Bayes classifier, missing data items are
Q21 | This clustering algorithm merges and splits nodes to help modify nonoptimal partitions.
Q22 | This clustering algorithm initially assumes that each data instance represents a single cluster.
Q23 | This unsupervised clustering algorithm terminates when mean values computed for the currentiteration of the algorithm are identical to the computed mean values for the previous iteration.
Q24 | Machine learning techniques differ from statistical techniques in that machine learning methods
Q25 | In reinforcement learning if feedback is negative one it is defined as____.