When training a model, why should you randomly split the rows into separate subsets?

When training a model, why should you randomly split the rows into separate subsets?
A . to train the model twice to attain better accuracy
B . to train multiple models simultaneously to attain better performance
C . to test the model by using data that was not used to train the model

View Answer

Answer: C

Explanation:

The goal is to produce a trained (fitted) model that generalizes well to new, unknown data. The fitted model is evaluated using “new” examples from the held-out datasets (validation and test datasets) to estimate the model’s accuracy in classifying new data.

https://en.wikipedia.org/wiki/Training,_validation,_and_test_sets#:~:text=Training%20dataset,-A%20training%20dataset&text=The%20goal%20is%20to%20produce,accuracy%20in%20classifying%20new%20data.