Topic 1 Question 14
A company wants to develop an educational game where users answer questions such as the following: "A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?" Which solution meets these requirements with the LEAST operational overhead?
Use supervised learning to create a regression model that will predict probability.
Use reinforcement learning to train a model to return the probability.
Use code that will calculate probability by using simple rules and computations.
Use unsupervised learning to create a model that will estimate probability density.
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- 正解だと思う選択肢: C
Make it simple : Use code that will calculate probability by using simple rules and computations.
👍 4jove2024/11/05 - 正解だと思う選択肢: C
C: Use code that will calculate probability by using simple rules and computations.
Explanation: For a question like this, where the probability can be computed using basic arithmetic (e.g., number of favorable outcomes divided by total outcomes), implementing a straightforward function in code will meet the requirements with the least operational overhead. This avoids the complexity and resource demands of machine learning.
For example:
Total marbles = 6 + 4 + 3
13 6+4+3=13
👍 4Moon2024/12/30 - 正解だと思う選択肢: C
Not necessary to train a model for this. Code for computation is sufficient.
👍 3tccusa2024/11/03
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