ML Quiz Set 1

K-Nearest Neighbors (KNN) is classified as what type of machine learning algorithm?

• Instance-based learning
• Non-parametric learning
• Model-based learning
• Parametric learning

There is no upper bound on the number of the independent variable(s).

• True
• False

Threshold value is 0.5. h(x) = 0.7 for a particular instance. What is the value of y?

• 1
• 0.3
• 0.7

The original boosting method requires a very large training sample

• True
• False

39. Which one of the following applications is not an example of Naïve Bayes algorithm?

• Stock market forecasting
• Text classification
• Sentiment analysis
• Spam filtering

Which of the following statements is not true about boosting?

• It tries to generate complementary base-learners by training the next learner on the mistakes of the previous learners
• It mainly increases the bias and the variance
• It uses the mechanism of increasing the weights of misclassified data in preceding classifiers
• It is a technique for solving two-class classification problems

Let there be n features. What is the dimension of the X vector in hypothesis h(X) = tTX?

• n x 1
• (n + 1) x 1
• (n – 1) x 1
• n x n

Can a cancer detection problem be solved by logistic regression?

• It is a supervised learning algorithm
• Ensembles can be shown to have more flexibility in the functions they can represent
• More random algorithms can be used to produce a stronger ensemble

Given three training instances with weights 0.5, 0.2, 0.04. The predicted values are 1, 1, and – 1. The actual output variables in the instances are – 1, 1, and 1. And the terror would be 1, 0, and 1. What is the misclassification rate?

• 0.71
• 0.73
• 0.5
• 0.65

What is the objective of backpropagation algorithm?

• to develop learning algorithm for multilayer feedforward neural network
• to develop learning algorithm for multilayer feedforward neural network, so that network can be trained to capture the mapping implicitly
• none of the mentioned
• to develop learning algorithm for single layer feedforward neural network