Question
Why do we want to avoid overfitting despite of its perfect performance on training data? Group of answer choices.
1. It fails on validation data 2.We do not want to avoid overfitting, we want to see the best fit on training data
3.None
4. It fails on testing data
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution
Trending nowThis is a popular solution!
Step by stepSolved in 4 steps
Knowledge Booster
Similar questions
- Only by seeing how well a model performs on test data can its accuracy be determined. elaborate on; provide additional information about Explain?arrow_forwardHow does regression testing operate, and what does it entail? Explain how regression testing is made easier using automated tests and a testing framework like JUnit.arrow_forwardWrite the objectives of regression testing and what are the situations to perform regression testing?arrow_forward
- Explain the difference between training and testing error.arrow_forwardDescribe how Automated Regression Testing will be conducted. Who will write the test scripts for the testing, what would be sequence of events of Automated Regression Testing, and how will the testing activity take place?arrow_forwardDo you have any suggestions for special strategies that may be used in order to record the flow of data?arrow_forward
- What's the difference between a tabular analysis and a virtual one while looking at data?arrow_forwardProvide definitions for the terms error, fault, and failure in simple English. What exactly is a test oracle, and how does it function in practice? What is it that is being tested, exactly? Who is to blame, and what is the significance of this development?arrow_forwardMake sure to explain the difference between Data Driven Testing and Retesting.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios