Question

When building a predictive model, what is the goal of the training phase?

A: To adjust training methods from backpropagation to supervised learning to see how that affects outputs
B: To use the model in real-world scenarios, monitoring performance
C: To adjust the model based on a subset of data, optimizing for a lower error rate
D: To specify the type of algorithm the model should use and make sure the data is cleaned/formatted

Answer 1

The goal of the training phase when building a predictive model is to adjust the model based on a subset of data, optimizing for a lower error rate.

Step-by-step explanation:

The goal of the training phase when building a predictive model is to adjust the model based on a subset of data, optimizing for a lower error rate. During the training phase, the model is presented with a labeled dataset and it learns to recognize patterns and make predictions based on that data. By minimizing the error rate on the training data, the model becomes more accurate and reliable in making predictions on new, unseen data.