Garch - Study guides, Class notes & Summaries
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ISYE 6501 MIDTERM 1 VERIFIED EXAM TEST
- Exam (elaborations) • 2 pages • 2024
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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 Midterm 1 QUESTIONS CORRECTLY ANSWERED LATEST UPDATE Support Vector Machine(SVM) is a supervised machine learnin
- Exam (elaborations) • 7 pages • 2023
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ISYE 6501 Midterm 1 
QUESTIONS CORRECTLY 
ANSWERED LATEST UPDATE 
Support Vector Machine(SVM) is a supervised machine learning 
algorithm used for? - ANSWER Classification 
How to split the data if we only have one model? - ANSWER 
70% training data, 30% testing data 
How to split the data if we want to compare models? - ANSWER 
70% training, 15% validation and 15% testing 
When do we need to do scaling in data? - ANSWER When our 
factors/attributes/dimensions are orders of magnitude differe...
-
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 - Midterm 1 2024 with complete verified solutions.
- Exam (elaborations) • 25 pages • 2024
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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 QUESTIONS CORRECTLY ANSWERED LATEST UPDATE
- Exam (elaborations) • 7 pages • 2024
- Available in package deal
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- $12.99
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ISYE 6501 Midterm 1 
QUESTIONS CORRECTLY 
ANSWERED LATEST UPDATE 
Support Vector Machine(SVM) is a supervised machine learning 
algorithm used for? - ANSWER Classification 
How to split the data if we only have one model? - ANSWER 
70% training data, 30% testing data 
How to split the data if we want to compare models? - ANSWER 
70% training, 15% validation and 15% testing 
When do we need to do scaling in data? - ANSWER When our 
factors/attributes/dimensions are orders of magnitude differe...
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SYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered
- Exam (elaborations) • 17 pages • 2024
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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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GT Students and Verified Midterm Exam with complete solution Latest March 2023.
- Exam (elaborations) • 27 pages • 2023
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GT Students and Verified Midterm Exam with complete solution Latest March 2023. 
GT STUDENTS AND VERIFIED 
Downloaded by: spark | 
Distribution of this document is illegal 
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3/3/2023 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX 

Good Luck! 
Question 0 -- Practice with Drag & Drop 
0 points possible (ungraded) 
 Keyboard Help 
Some of the quiz questions are Drag-and-Drop. You'll need to drag one or more answers 
to a location. 
Some an...
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ISYE 6501 MIDTERM 1 VERIFIED EXAM TEST
- Exam (elaborations) • 2 pages • 2024
- Available in package deal
-
- $12.49
- + learn more
ISYE 6501 MIDTERM 1 VERIFIED EXAM 
TEST 
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 - ...
-
ISYE 6501 - Final Prep – Midterm Questions With Correct Answers
- Exam (elaborations) • 3 pages • 2023
- Available in package deal
-
- $7.99
- + learn more
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
-
ISYE 6501 Midterm 1 QUESTIONS CORRECTLY ANSWERED LATEST UPDATE
- Exam (elaborations) • 7 pages • 2023
- Available in package deal
-
- $8.99
- + learn more
ISYE 6501 Midterm 1 
QUESTIONS CORRECTLY 
ANSWERED LATEST UPDATE 
Support Vector Machine(SVM) is a supervised machine learning 
algorithm used for? - ANSWER Classification 
How to split the data if we only have one model? - ANSWER 
70% training data, 30% testing data 
How to split the data if we want to compare models? - ANSWER 
70% training, 15% validation and 15% testing 
When do we need to do scaling in data? - ANSWER When our 
factors/attributes/dimensions are orders of magnitude differe...
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