[amp_mcq option1=”Representation scheme used” option2=”Training scenario” option3=”Type of feedback” option4=”Good data structures” correct=”option4″]
The correct answer is D. Good data structures.
The other options are all factors that can affect the performance of a learner system.
- Representation scheme used: The representation scheme used to encode the knowledge in the learner system can have a significant impact on its performance. For example, a system that uses a symbolic representation scheme may be more efficient than a system that uses a neural network representation scheme.
- Training scenario: The training scenario used to train the learner system can also have a significant impact on its performance. For example, a system that is trained on a large dataset of labeled data may be more accurate than a system that is trained on a small dataset of unlabeled data.
- Type of feedback: The type of feedback that is provided to the learner system can also have a significant impact on its performance. For example, a system that is given positive feedback when it makes correct predictions may be more likely to learn than a system that is given negative feedback when it makes incorrect predictions.
Good data structures are important for the efficiency of a learner system, but they do not directly affect its accuracy. A learner system can be accurate even if it uses poor data structures, and it can be inefficient even if it uses good data structures.