What is the process of removing unnecessary weights from a trained perceptron called?Select one:a.Pruningb.Trainingc.Validationd.Testing
Question
What is the process of removing unnecessary weights from a trained perceptron called?
Select one:
- a. Pruning
- b. Training
- c. Validation
- d. Testing
Solution
Answer:
The process of removing unnecessary weights from a trained perceptron is called a. Pruning.
Explanation:
Pruning is a technique used in machine learning and neural networks to reduce the size of the model by eliminating weights that contribute little to the model's output. This is typically done after the training phase to simplify the model, enhance performance, and reduce the potential for overfitting. The other options do not pertain to this specific action:
- b. Training refers to the process of teaching a model using data.
- c. Validation is a method of assessing the model's performance on a set of data that was not used during training.
- d. Testing involves evaluating the final model on a completely independent dataset to ascertain its performance.
Thus, the correct choice is pruning.
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