Machine Learning MCQ Questions: Practice and Test Your Knowledge
Ace your exams, tests, interviews, and quizzes with our comprehensive set of Machine Learning Multiple Choice Questions (MCQs). Covering essential topics in Machine Learning, enhance your understanding and boost your performance. Start practicing now Page-10 section-3
Each section contains 100 MCQs on
Machine Learning .
Suppose we train a hard-margin linear SVM on n > 100 data points in R2, yielding a hyperplane with exactly 2 support vectors. If we add one more data point and retrain the classifier, what is the maximum possible number of support vectors for the new hyperplane (assuming the n + 1 points are linearly separable)?
Which of the following can be true for selecting base learners for an ensemble? 1. Different learners can come from same algorithm with different hyper parameters 2. Different learners can come from different algorithms 3. Different learners can come from different training spaces
Suppose you have fitted a complex regression model on a dataset. Now, you are using Ridge regression with tuning parameter lambda to reduce its complexity. Choose the option(s) below which describes relationship of bias and variance with lambda.
You've just finished training a decision tree for spam classification, and it is getting abnormally bad performance on both your training and test sets. You know that your implementation has no bugs, so what could be causing the problem?
Which of the following properties are characteristic of decision trees? 1. High bias 2. High variance 3. Lack of smoothness of prediction surfaces 4. Unbounded parameter set
