Explanation: Reinforcement learning is the type of learning in which teacher returns award or punishment to learner. 7. Decision trees are appropriate for the problems where:
A. Attributes are both numeric and nominal
B. Target function takes on a discrete number of values.
C. Data may have errors
D. All of the mentioned
Answer:A
Explanation: Reinforcement learning is the type of learning in which teacher returns award or punishment to learner. 7. Decision trees are appropriate for the problems where:
A. Attributes are both numeric and nominal B. Target function takes on a discrete number of values. C. Data may have errors D. All of the mentioned
Explanation: Decision trees can be used in all the conditions stated. 8. Which of the following is not an application of learning?