K means clustering Samenvattingen, Aantekeningen en Examens

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ISYE 6501 - Introduction to  Analytics Weeks 1 – 7 Combined Frequent Exam  Questions Correctly Answered
  • ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered

  • Tentamen (uitwerkingen) • 17 pagina's • 2023
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  • ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered Support Vector Machine (SVM) - ANSWER Supervised learning classification tool and algorithm that seeks a dividing hyperplane for any number of dimensions can be used for regression or classification. Margin of Error (SVM) - ANSWER A small margin for error reduces your chances of misclassifying known data points but increases your chances of misclassifying unknown data points. ...
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MIST 6360 Final Exam Correct Questions and Answers!!
  • MIST 6360 Final Exam Correct Questions and Answers!!

  • Tentamen (uitwerkingen) • 14 pagina's • 2024
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  • Data Science - ANSWER interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured 3 Analytical Approaches to Predictive Analytics - ANSWER Statistics, Artificial Intelligence, Machine Learning Statistics - ANSWER the foundation for predictive analytics -- the building blocks Ex: regression, factor & cluster analysis Artificial Intelligence - ANSWER uses heuristics- "rules of t...
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ISYE 6501 FINAL ACTUAL EXAM (UPDATED QUESTIONS AND ANSWERS)
  • ISYE 6501 FINAL ACTUAL EXAM (UPDATED QUESTIONS AND ANSWERS)

  • Tentamen (uitwerkingen) • 33 pagina's • 2024
  • What do descriptive questions ask? - CORRECT ANSWER-What happened? (e.g., which customers are most alike) What do predictive questions ask? - CORRECT ANSWER-What will happen? (e.g., what will Google's stock price be?) What do prescriptive questions ask? - CORRECT ANSWER-What action(s) would be best? (e.g., where to put traffic lights) What is a model? - CORRECT ANSWER-Real-life situation expressed as math. What do classifiers help you do? - CORRECT ANSWER-differentiate What is a soft...
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SRM EXAM STUDYGUIDE LATEST UPDATE
  • SRM EXAM STUDYGUIDE LATEST UPDATE

  • Tentamen (uitwerkingen) • 25 pagina's • 2023
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  • SRM EXAM STUDYGUIDE LATEST UPDATE...
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ISYE 6501 - Midterm 1 2024 with complete verified solutions.
  • ISYE 6501 - Midterm 1 2024 with complete verified solutions.

  • Tentamen (uitwerkingen) • 25 pagina's • 2024
  • What do descriptive questions ask? What happened? (e.g., which customers are most alike) What do predictive questions ask? What will happen? (e.g., what will Google's stock price be?) Brainpower Read More 0:05 / 0:15 What do prescriptive questions ask? What action(s) would be best? (e.g., where to put traffic lights) What is a model? Real-life situation expressed as math. What do classifiers help you do? differentiate What is a soft classifier and when is it...
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ISYE 6501 MIDTERM 1 EXAM TEST
  • ISYE 6501 MIDTERM 1 EXAM TEST

  • Tentamen (uitwerkingen) • 20 pagina's • 2024
  • What do descriptive questions ask? - CORRECT ANSWER-What happened? (e.g., which customers are most alike) What do predictive questions ask? - CORRECT ANSWER-What will happen? (e.g., what will Google's stock price be?) What do prescriptive questions ask? - CORRECT ANSWER-What action(s) would be best? (e.g., where to put traffic lights) What is a model? - CORRECT ANSWER-Real-life situation expressed as math. What do classifiers help you do? - CORRECT ANSWER-differentiate What is a soft...
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ISYE 6501 MIDTERM 1 VERIFIED EXAM  TEST
  • ISYE 6501 MIDTERM 1 VERIFIED EXAM TEST

  • Tentamen (uitwerkingen) • 2 pagina's • 2024
  • Matching models/methods to categories - CORRECT ANSWER-(cusum and pca = NONE) Select all of the following models that are designed for use with attribute/feature data (i.e., not time-series data): - CORRECT ANSWER-k-nearest-neighbor, PCA, k-means, logistic regression, linear regression, random forest, SVM's Classification models - CORRECT ANSWER-CART, k-nearest-neighbor, logistic regression, random forest, support vector machine Clustering - CORRECT ANSWER-k-means Response predictio...
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ISYE 6501 Practice Test Questions With Correct Answers
  • ISYE 6501 Practice Test Questions With Correct Answers

  • Tentamen (uitwerkingen) • 11 pagina's • 2023
  • ISYE 6501 Practice Test Questions With Correct Answers Algorithm - CORRECT ANSWER Step by step procedure designed to carry out a task Change Detection - CORRECT ANSWER Identifying when a significant change has taken place in a process. Classification - CORRECT ANSWER The separation of data into two or more categories or (a point's classification) the category a data point is put into Classifier - CORRECT ANSWER A bou...
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QUESTIONS AND ANSWERS FOR ISYE  6501 FINAL
  • QUESTIONS AND ANSWERS FOR ISYE 6501 FINAL

  • Tentamen (uitwerkingen) • 8 pagina's • 2024
  • Support Vector Machine - CORRECT ANSWER-A supervised learning, classification model. Uses extremes, or identified points in the data from which margin vectors are placed against. The hyperplane between these vectors is the classifier SVM Pros/Cons - CORRECT ANSWER-Pros: It works really well with a clear margin of separation It is effective in high dimensional spaces. It is effective in cases where the number of dimensions is greater than the number of samples. It uses a subset of tra...
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ISYE 6501 - Introduction to  Analytics Weeks 1 – 7 Combined Frequent Exam  Questions Correctly Answered
  • ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered

  • Tentamen (uitwerkingen) • 17 pagina's • 2023
  • ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered Support Vector Machine (SVM) - ANSWER Supervised learning classification tool and algorithm that seeks a dividing hyperplane for any number of dimensions can be used for regression or classification. Margin of Error (SVM) - ANSWER A small margin for error reduces your chances of misclassifying known data points but increases your chances of misclassifying unknown data points. ...
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