What are the ways to avoid overfitting issues in data science? By adding a penalty for every data decreasing the complexity By testing the model with one-third of the training data itself By using the re-sampling techniques to estimate model accuracy All of the above

What are the ways to avoid overfitting issues in data science? By

1.	What are the ways to avoid overfitting issues in data science? By adding a penalty for every data decreasing the complexity By testing the model with one-third of the training data itself By using the re-sampling techniques to estimate model accuracy All of the above
Answer» E.....! here is your ANSWER...,,, What are the WAYS to avoid overfitting issues in data science?=>By using the re-sampling techniques to ESTIMATE model accuracyhopes help.