(a) This question is about knowledge discovery from data by machine learning. The data samples given in the table below

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A This Question Is About Knowledge Discovery From Data By Machine Learning The Data Samples Given In The Table Below 1 (92.57 KiB) Viewed 13 times

(a) This question is about knowledge discovery from data by machine learning. The data samples given in the table below represent certain relationships between the Diagnosis result and the measurements of Blood Pressure, Pulse, and Body Temperature. Assume these data samples are very informative and among the three measurements Body Temperature is least relevant to Diagnosis. Blood Pressure Pulse Diagnosis Body Temperature High High 38 A Normal High 38 B Normal Normal 40 C High Normal 35 A Normal Normal 35 C Normal High 35 B High Normal 40 A High High 35 A (1) Find whether Blood Pressure or Pulse has the largest information gain about the Diagnosis result. (ii) Use information gain based decision tree induction method to get production rules (IF_THEN rules) as the knowledge that can be discovered or extracted from these data samples.
(b) In the following state transition diagram, the number alongside each arrow indicates the reward associated with the corresponding state transition, and state A is the goal state. If the discount factor is 0.9, calculate the maximum discounted cumulative reward values of state D and state E for reinforcement learning, respectively. A 100 50 C E 0 F B D
(a) Based on your understanding of the two AI tests: Turing Test and Robot College Student Test, with no more than 100 words propose an AI test using a Metaverse scenario. (b) The A* search strategy uses both the cost of reaching the current state from the initial state and an estimate of the cost of reaching the goal state from the current state to select nodes for expansion. It estimates the cost of reaching the goal state from the current state using a heuristic. (i) If the heuristic is faulty and always returns a value of 1000, what search strategy is this A* search equivalent to? (ii) With such a faulty heuristic, is this A* search optimal and complete? (c) Answer the following questions about uncertainty representation and reasoning in production systems using the Mycin's certainty factor system: (i) If condition I is satisfied with certainty 0.9 and condition 2 is satisfied with certainty 0.7, what is the certainty with which condition 1 AND condition 2 is satisfied? (ii) If a conclusion can be drawn from Rule 1 with certainty 0.8 and the same conclusion can also be drawn from Rule 2 with certainty 0.5, what is the certainty with which this conclusion can be drawn by using both Rule 1 and Rule 2?