solved CLC – Calibration and External Validation Literature ReviewStep 1:undefinedReview the

CLC – Calibration and External Validation Literature ReviewStep 1:undefinedReview the article, “Validate to Bring Out the Real Value of Visual Analytics,” (https://www.infosysblogs.com/testing-services/2016/04/validate_to_bring_out_the_real.html), for an in-depth understanding of expert validation, predictive validation, external validation, and cross validation.Step 2:Conduct a literature review of similar research to compare the model that you completed in Topic 5. Create a draft outline with the following items in your literature review.Complete an external and cross validation.Explain if your validation method is still sufficient and discuss if the model results are consistent with theories in your field.What are the next steps for your model? Be specific.Is there a need for a model revision? If so, describe what shortcomings you encountered. If not, describe why.What future recommendations would you make to your model if you had another opportunity? What would you do differently?You are required to include at least three scholarly peer-reviewed sources.Step 3:Synthesize the information from the draft outline to complete, the relevant components of the External Model Verification and Calibration section of the “Capstone Project Thesis Template.” This should be 750-1,000 words.Needed for Submission Requirements:Draft OutlineUpdated “Capstone Project Thesis Template.” – External Model Verification and CalibrationStep 4: Reflection Questions (separate from above)Due: 5/15/2021Question 1 – Before adopting and implementing your prediction model, the generalizability of the model needs to be assessed by an external validation. Discuss the strength of your model and issues you might encounter in the external validation process.Due 5/17/2021Question 2 – What changes to your model would you entertain if all the external literature concludes diametrically opposed recommendations from your modeling effort?