Question

Which of the following statements is not true?

1.Even after the application of a variable selection technique, underfitting is still a possibility
2.Always keep the model as complicated as possible, keeping all variables with significant coefficients
3.If you have a good performance in the training set but poor performance in the test set, you may have a problem with overfitting
4.Even after the application of a variable selection technique, overfitting is still a possibility

Answer 1

The statement that is not true is: Always keep the model as complicated as possible, keeping all variables with significant coefficients.

Step-by-step explanation:

The statement that is not true is option b: Always keep the model as complicated as possible, keeping all variables with significant coefficients.

It is not always necessary to keep the model complicated and include all variables with significant coefficients. In fact, including unnecessary variables in a model can lead to overfitting, where the model performs well on the training set but poorly on the test set. An important step in model building is to apply a variable selection technique to identify the most important and relevant variables for the model, which can help prevent overfitting. However, even after variable selection, underfitting or overfitting is still possible.