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ISYE 6501 Midterm 1 EXAM  QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST  UPDATE 2023/2024
  • ISYE 6501 Midterm 1 EXAM QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST UPDATE 2023/2024

  • Exam (elaborations) • 8 pages • 2024
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  • ISYE 6501 Midterm 1 EXAM QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST UPDATE 2023/2024 True or false: In a regression tree, every leaf of the tree has a different regression model that might use different attributes, have different coefficients, etc. - ANSWER True - Each leaf's individual model is tailored to the subset of data points that follow all of the branches leading to the leaf. True or false: Tree-based approaches can be used for other models besides regression. - ANSW...
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ISYE 6501 Midterm 1 EXAM  QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST  UPDATE 2023/2024
  • ISYE 6501 Midterm 1 EXAM QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST UPDATE 2023/2024

  • Exam (elaborations) • 8 pages • 2024
  • Available in package deal
  • ISYE 6501 Midterm 1 EXAM QUESTIONS WITH VERIFIED SOLUTIONS 100% LATEST UPDATE 2023/2024 True or false: In a regression tree, every leaf of the tree has a different regression model that might use different attributes, have different coefficients, etc. - ANSWER True - Each leaf's individual model is tailored to the subset of data points that follow all of the branches leading to the leaf. True or false: Tree-based approaches can be used for other models besides regression. - ANSW...
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ISYE 6501 - Final Prep – Midterm Questions With  Correct Answers
  • ISYE 6501 - Final Prep – Midterm Questions With Correct Answers

  • Exam (elaborations) • 3 pages • 2024
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  • ISYE 6501 - Final Prep – Midterm Questions With Correct Answers Types of classification models KNN SVM Types of Clustering Models K-Means Clustering Types of Response Prediction Models ARIMA CART Exponential Smoothing Linear Regression Logistic Regression Random Forest Types of Validation Method Cross Validation Types of Variation Estimate Models GARCH Models that use Time Series Data ARIMA CUSUM GARCH Exponential Smoothing Do models tend to perform better or worse on ...
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ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed
  • ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed

  • Exam (elaborations) • 2 pages • 2024
  • Types of classification models Correct Answer-KNN SVM Types of Clustering Models Correct Answer-K-Means Clustering Types of Response Prediction Models Correct Answer-ARIMA CART Exponential Smoothing Linear Regression Logistic Regression Random Forest Types of Validation Method Correct Answer-Cross Validation Types of Variation Estimate Models Correct Answer-GARCH Models that use Time Series Data Correct Answer-ARIMA CUSUM GARCH Exponential Smoothing Do models tend to perform bette...
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ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed
  • ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed

  • Exam (elaborations) • 2 pages • 2024
  • Types of classification models Correct Answer-KNN SVM Types of Clustering Models Correct Answer-K-Means Clustering Types of Response Prediction Models Correct Answer-ARIMA CART Exponential Smoothing Linear Regression Logistic Regression Random Forest Types of Validation Method Correct Answer-Cross Validation Types of Variation Estimate Models Correct Answer-GARCH Models that use Time Series Data Correct Answer-ARIMA CUSUM GARCH Exponential Smoothing Do models tend to perform bette...
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Isye 6501 Final Exam Latest 2021 Already Passed
  • Isye 6501 Final Exam Latest 2021 Already Passed

  • Exam (elaborations) • 32 pages • 2024
  • 1-norm Correct Answer-Similar to rectilinear distance; measures the straight-line length of a vector from the origin. If z=(z1,z2,...,zm) is a vector in an m-dimensional space, then it's 1-norm is square root(|
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Isye 6501 Final Exam Latest 2021 Already Passed
  • Isye 6501 Final Exam Latest 2021 Already Passed

  • Exam (elaborations) • 32 pages • 2024
  • 1-norm Correct Answer-Similar to rectilinear distance; measures the straight-line length of a vector from the origin. If z=(z1,z2,...,zm) is a vector in an m-dimensional space, then it's 1-norm is square root(|
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ISYE 6501 Final Questions and Answers Latest Update
  • ISYE 6501 Final Questions and Answers Latest Update

  • Exam (elaborations) • 14 pages • 2024
  • Factor Based Models Correct Answer-classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model Why limit number of factors in a model? 2 reasons Correct Answer-overfitting: when # of factors is close to or larger than # of data points. Model may fit too closely to random effects simplicity: simple models are usually better Classical variable selection approaches Correct Answer-1. Forward selection 2. Backwards elimination 3. Stepwise regress...
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ISYE 6501 Final Questions and Answers Latest Update
  • ISYE 6501 Final Questions and Answers Latest Update

  • Exam (elaborations) • 14 pages • 2024
  • Factor Based Models Correct Answer-classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model Why limit number of factors in a model? 2 reasons Correct Answer-overfitting: when # of factors is close to or larger than # of data points. Model may fit too closely to random effects simplicity: simple models are usually better Classical variable selection approaches Correct Answer-1. Forward selection 2. Backwards elimination 3. Stepwise regress...
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ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed
  • ISYE 6501 - Final Prep - Midterm 1 and 2 Review Latest Update Already Passed

  • Exam (elaborations) • 2 pages • 2024
  • Types of classification models Correct Answer-KNN SVM Types of Clustering Models Correct Answer-K-Means Clustering Types of Response Prediction Models Correct Answer-ARIMA CART Exponential Smoothing Linear Regression Logistic Regression Random Forest Types of Validation Method Correct Answer-Cross Validation Types of Variation Estimate Models Correct Answer-GARCH Models that use Time Series Data Correct Answer-ARIMA CUSUM GARCH Exponential Smoothing
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