41. In reinforcement learning, this feedback is usually called as . . . . . . . .
42. In multiclass classification number of classes must be
43. Which of the following methods can not achieve zero training error on any linearly separable dataset?
44. Imagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case?
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.
45. Which of the following evaluation metrics can be used to evaluate a model while modeling a continuous output variable?
46. SVM is a algorithm
47. Which of the one is true about Heteroskedasticity?
48. Suppose that we have N independent variables (X1, X2, Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of its variable(Say X1) with Y is -0.95. Which of the following is true for X1?
49. While using feature selection on the data, is the number of features decreases.
50. Dimensionality Reduction Algorithms are one of the possible ways to reduce the computation time required to build a model
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