What is the process of using a backpropagation network to make predictions called?Select one:a.Testingb.Trainingc.Inferringd.Validating

Break Down the Problem

1. Identify the key terms in the question: backpropagation network, predictions, and the options provided.
2. Understand the context in which a backpropagation network is used.

Relevant Concepts

1. A backpropagation network is a type of artificial neural network that learns from the error it makes in its predictions by adjusting the weights through a process called backpropagation.
2. The options provided refer to different phases or activities related to machine learning models.

Analysis and Detail

1. Training: This is the process where the model learns from the training data by adjusting weights to minimize the prediction error.
2. Testing: This phase evaluates how well the model performs on unseen data to assess its generalization ability.
3. Inferring: This refers to using the trained model to make predictions on new data.
4. Validating: This is the stage where the model's performance is assessed on a validation set during training to tune hyperparameters.

Verify and Summarize

In the context of backpropagation networks, the process of making predictions after training has been completed is termed inferring. Since the question specifically refers to making predictions, the correct choice is:

Final Answer

c. Inferring