In a Naive Bayes classifier, you are given the following probabilities: P(Class A) = 0.4 P(Class B) = 0.6 P(Feature X | Class A) = 0.5 P(Feature X | Class B) = 0.5 If Feature X is observed, which class is the sample more likely from and with what normalized probability?

Which parameter(s) of a 1-D Gaussian mixture model has a constraint to sum to one?

In the context of Gaussian Mixture Models, what is the main difference between the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) when selecting the optimal number of components?

____ aims to decrease ____ while ____ aims to decrease ____.

These values {outstanding, above average, average, below average, unacceptable} are values assigned to nominal categorical variables. 

The following eigenvalues are computed from a centered dataset: 17, 10, 8, 6, 5, 3, and 1.  What is the minimum dimension needed to achieve a ratio of total variance of at least 90%?

DBSCAN seeks to find the maximal set of ____ points.

What is the total numbers of parameters to estimate for a Gaussian Mixture Model with full covariance matrices and k clusters on a dataset with d features?

In Principal Component Analysis (PCA), which of the following best describes the role of the principal components?

You are a new hire for a laptop repair company. Your boss wants you to classify if a laptop is functional, broken, or impaired. If you select Naive Bayes as the classifier for your machine learning framework (shown below) and you have data recorded from previous test performed on a small number of laptops, which learning algorithm should you use to update the model?