Reference no: EM131960387
Assignment
Answer each of the questions (you write it by hand on paper).
1. Give the formal definition of "Learning". What are the six issues in machine learning?
2. Define "concept learning". Give an example and explain it.
3. What is the inductive learning hypothesis? Explain the term more_general_than_or_equal_to with an example?
4. Write the Find-S algorithm.Explain it with an example.
5. What are the four main questions unanswered by the Find-S algorithm? Give the List-Then-Eliminate algorithm.
6. Define the terms, the version space, the general boundary, the specific boundary. State the version space representation theorem.
7. Write the candidate-elemination algorithm.
8. Define Inductive bias. Explain the inductive bias in the context of the three algorithms, Rote-learner, Candidate-elimination and Find-S.
9. Explain in your own words how do you quantify "the amount of information" in a message, with an example. Define what is entropy in information theory.