Training Q13

Predicting the amount of rainfall in a region based on various cues is a ______ problem.

• Supervised learning

• Unsupervised learning

• Clustering

• None

A and B are two events. If P(A, B) decreases while P(A) increases, which of the following is true?

• P(A|B) decreases

• P(B|A) decreases

• P(B) decreases

• All

Which of the following is NOT supervised learning?

• PCA

• Decision Tree

• Linear Regression

• Naive Bayesian

Which of the following statements about Naive Bayes is incorrect?

• Attributes are equally important.

• Attributes are statistically dependent of one another given the class value.

• Attributes are statistically independent of one another given the class value.

• Attributes can be nominal or numeric

As the number of training examples goes to infinity, your model trained on that data will have:

• Lower variance

• Higher variance

• Same variance

• None

Given two Boolean random variables, A and B, where P(A) = ½, P(B) = 1/3, and P(A | ¬B) = ¼, what is P(A | B)?

• 1/6

• 1/4

• 3/4

• 1

 ___________ refers to a model that can neither model the training data nor generalize to new data.

• good fitting

• overfitting

• underfitting

• All

Which of the following is more appropriate to do feature selection?

• Ridge

• Lasso

• Both

• None

Which one of the following is the main reason for pruning a Decision Tree?

• To save computing time during testing

• To save space for storing the Decision Tree

• To make the training set error smaller

• To avoid overfitting the training set

Decision trees can work with

• Only numeric values

• Only nominal values

• Both numeric and nominal values

• None