K fold cross validation - Samenvattingen, Aantekeningen en Examens
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ISYE 6501 MIDTERM 1 COMPLETE EXAM WITH UPGRADED QUESTIONS AND ANSWERS
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ISYE 6501 MIDTERM 1 COMPLETE 
EXAM WITH UPGRADED QUESTIONS 
AND ANSWERS 
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...
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Georgia Tech WEEK 2 HOMEWORK – SAMPLE SOLUTIONS IMPORTANT NOTE, Rated A+, 2022.
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Georgia Tech WEEK 2 HOMEWORK – SAMPLE SOLUTIONS IMPORTANT NOTE, Rated A+, 2022. 
Document Content and Description Below 
WEEK 2 HOMEWORK – SAMPLE SOLUTIONS IMPORTANT NOTE These homework solutions show multiple approaches and some optional extensions for most of the questions in the assignment. You don’t need to s ubmit all this in your assignments; they’re included here just to help you learn more – because remember, the main goal of the homework assignments, and of the entire course, ...
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ISYE 6501 Final with 100% correct answers
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Support Vector Machine 
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 
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 training points in the decision funct...
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SAS Advanced Analytics Exam 2 Questions and 100% Correct Answers
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Which of the following is the key limitation of the simple perceptron? - It can solve only linearly separable problems 
 
In theory, a polynomial regression model of sufficient complexity is a universal approximator. (T/F)? - true 
 
Even after training is completed, neural networks are usually slow to generate their estimates/decisions. (T/F)? - false 
 
A linear perceptron is a nonlinear model. (T/F)? - false 
 
The addition of direct connections between the input and output layers...
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ISYE 6501 Final Exam Questions with Correct Answers
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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 training poin...
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Machine Learning Exam with perfect answers
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Supervised Learning correct answers Training of a ML model using datasets with labels 
 
Unsupervised Learning correct answers Training of a ML model without labeled datasets 
 
Training Set correct answers Set of data with labels and features used to teach the ML model/determine its parameters 
 
Validation Set correct answers Set used during training to fine tune the model's parameters/determine its hyperparameters & evaluate the model's performance 
 
Testing Set correct answers Used a...
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GEORGIA Tech, ISYE Full course, Graded A+, 2022 update
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GEORGIA Tech, ISYE Full course, Graded A+, 2022 update 
Document Content and Description Below 
Week 1 Why Analytics? 6 Data Vocabulary 7 Classification 8 Support Vector Machines 11 Scaling and Standardization 13 k-Nearest Neighbor (KNN) 13 Week 2 Model Validation 16 Validation and Test Sets 17 Splitting the Data 18 Cross-Validation 20 Clustering 21 Supervised vs. Unsupervised Learning 22 Week 3 Data Preparation 25 Introduction to Outliers 25 Change Detection 27 Week 4 Time Series Data 31 AutoRe...
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ISYE 6501 EXAM QUESTIONS WITH 100% SOLUTIONS 2024
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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 different such as income vs. 
credit score (income is much much larger) 
Whic...
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ISYE 6501 Midterm 1 QUESTIONS CORRECTLY ANSWERED LATEST UPDAT
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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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Georgia Tech ISYE Midterm 1 Notes: Week 1 Classification:, Graded A+
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Georgia Tech ISYE Midterm 1 Notes: Week 1 Classification:, Graded A+ 
Document Content and Description Below 
ISYE Midterm 1 Notes: Week 1 Classification: - Two main types of classifiers: o Hard Classifier: A classifier that perfectly separates data into 2 (or more) correct classes. This type of classifie r is rigid and is only applicable to perfectly separable datasets. o Soft Classifier: A classifier that does not perfectly separate data into perfectly correct classes. This type is used when a...
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