Discriminative vs Generative Models: Foundations Quiz Quiz

1. Identifying Model Types

   Which of the following is an example of a generative model?

   1. A. Naive Bayes
   2. B. Logistic Regression
   3. C. Decision Tree
   4. D. Support Vector Machine
   5. E. Ridge Regression

2. Understanding Discriminative Models

   Discriminative models are primarily used to model which probability?

   1. A. P(x)
   2. B. P(y)
   3. C. P(x|y)
   4. D. P(y|x)
   5. E. P(z|x)

3. Modeling Joint Probability

   Generative models are able to model which joint probability distribution?

   1. A. P(y|x)
   2. B. P(x|y)
   3. C. P(x, y)
   4. D. P(y-x)
   5. E. P(x/y)

4. Selecting Approaches

   If your goal is to generate new samples similar to your input data, which type of model should you prefer?

   1. A. Discriminative Model
   2. B. Generative Model
   3. C. Correlative Model
   4. D. Integrative Model
   5. E. Descriptive Model

5. Distinguishing Example Algorithms

   Which algorithm is a classic example of a discriminative model?

   1. A. Gaussian Mixture Model
   2. B. k-Nearest Neighbors
   3. C. Hidden Markov Model
   4. D. Logistic Regression
   5. E. Principal Component Analysis

6. Application Scenarios

   A spam classifier that draws a clear boundary between 'spam' and 'not spam' messages is most likely applying which type of model?

   1. A. Discriminative Model
   2. B. Generative Model
   3. C. Descriptive Model
   4. D. Predictive Model
   5. E. Unsupervised Model

7. Learning Differences

   Which statement best describes the main difference between discriminative and generative models?

   1. A. Discriminative models model P(x), while generative models model P(y)
   2. B. Discriminative models learn the boundary between classes, while generative models try to learn how the data is produced
   3. C. Discriminative models generate data samples, while generative models only classify data
   4. D. Discriminative models require more data than generative models
   5. E. Discriminative models are always more accurate than generative models

8. Generative Model Capabilities

   Which of the following tasks can generative models perform that discriminative models typically cannot?

   1. A. Estimating P(y|x)
   2. B. Predicting class labels
   3. C. Generating new data samples
   4. D. Clustering existing data
   5. E. Reducing dimensionality

9. Terminology Clarification

   What does the term 'discriminative' imply about how a model operates?

   1. A. It generates realistic data points
   2. B. It models the entire input probability distribution
   3. C. It distinguishes between different categories based on input features
   4. D. It clusters similar data points together
   5. E. It reduces noise in the input data

10. Generalization Focus

    Which statement accurately describes when you should choose a discriminative model over a generative model?

    1. A. When you need to model how the data was generated from classes
    2. B. When you want to maximize classification accuracy for a given input
    3. C. When you require synthetic data generation
    4. D. When your dataset is completely unlabeled
    5. E. When you need to compress the data