## which one of the following functions defines the relationship between a random and a systematic component?

1. From the given options, which regression type is an extension of the linear regression model that uses a link function?

(a) Generalised linear model (b) Non-linear regression model

(c) Logistics regression model (d) None of the above

2. From the given options, which one of the following functions defines the relationship

between a random and a systematic component?

(a) Logit function (b) User-defined function

(c) Link function (d) None of the above

3. From the given options, which regression is an extension of linear regression to environments

that contain a categorical dependent variable?

(a) Generalised linear model (b) Non-linear regression

(c) Logistics regression (d) None of the above

### Compute the information gain of the term “elections” according to Eq. 5.7.

Consider the term “elections” which is present in only 50 documents in a corpus of 1000 documents. Furthermore, assume that the corpus contains 100 documents belonging to the Politics category,….

### Predict the probabilities of categories Cat and Car of Test2 on the toy corpus example in Sect. 5.3.5.2. You can use the multinomial na¨ıve Bayes model with the same level of smoothing as used in the example in the book. Return normalized probabilities that sum to 1 over the two categories. 2.       Na¨ıve Bayes is a generative model in which each class corresponds to one mixture component. Design a fully supervised generalization of the nai¨ıve Bayes model in which each of the k classes contains exactly b > 1 mixture components for a total of b · k mixture components. How would you perform parameter estimation in this model?

1.       Predict the probabilities of categories Cat and Car of Test2 on the toy corpus example in Sect. 5.3.5.2. You can use the multinomial na¨ıve Bayes model with the same….

### What are the possible advantages and disadvantages of using such an approach?

1.       Na¨ıve Bayes is a generative model in which each class corresponds to one mixture component. Design a semi-supervised generalization of the nai¨ıve Bayes model in which each of the….