The use of cross-validation is appealing particularly when we have to design a l

Question

The use of cross-validation is appealing particularly when we have to design a large neural network with good generalization as the goal.” – Why we need cross-validation in addition to training and testing. The use of cross-validation is appealing particularly when we have to design a large neural network with good generalization as the goal.” – Why we need cross-validation in addition to training and testing. The use of cross-validation is appealing particularly when we have to design a large neural network with good generalization as the goal.” – Why we need cross-validation in addition to training and testing.

Explanation / Answer

Generally we do testing on our own sample data. With that sample data, we are only confined to a smaller amount of data.Using cross validation, we can check it's working on data sets other than our sample data i.e., over a large field. And can judge it's performance over accuracy and many other things.

Related Questions

Navigate

• Browse (All)
• Browse T
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.