DecodeAI
Sign inStart Learning
← Question Bank

Machine Learning

Probabilistic Modeling

Interview questions on Probabilistic Modeling.

8 questions

All subtopicsMaximum Likelihood EstimationMaximum A PosterioriNaive BayesLogistic Regression

Naive Bayes

Q1. Naive Bayes classifier.

Sign in to bookmark
  1. How is Naive Bayes classifier naive?
  2. Let’s try to construct a Naive Bayes classifier to classify whether a tweet has a positive or negative sentiment. We have four training samples: [TweetLabelThis makes me so upsetNegativeThis puppy makes me happyPositiveLook at this happy hamsterPositiveNo hamsters allowed in my houseNegative]\begin{bmatrix} \text{Tweet} & \text{Label} \\\\ \text{This makes me so upset} & \text{Negative}\\\\ \text{This puppy makes me happy} & \text{Positive} \\\\ \text{Look at this happy hamster} & \text{Positive} \\\\ \text{No hamsters allowed in my house} & \text{Negative} \end{bmatrix} According to your classifier, what's sentiment of the sentence The hamster is upset with the puppy?

Naive Bayes

Q4. Why is Naive Bayes still used despite its flawed assumption of feature independence?

Sign in to bookmark

Naive Bayes

Q5. What is Laplace smoothing (additive smoothing) in Naive Bayes?

Sign in to bookmark

Naive Bayes

Q6. Can Naive Bayes handle continuous and categorical features?

Sign in to bookmark

Naive Bayes

Q8. What is the difference between Naive Bayes and other classification algorithms like Logistic Regression or Decision Trees?

Sign in to bookmark