Multi armed bandit - Samenvattingen, Aantekeningen en Examens

A complete summary of all the lectures from Marketing Analytics for Big Data for the school year 2022/2023 at Tilburg University given by George Knox.

ISYE 6501 Midterm 2 Part 1 Latest 2023 Rated A greedy algorithm at each step, the algorithm does the thing that looks best without taking future options into consideration; more classical variable selection methods stepwise - (forward, backward, combination) lasso elastic net available metrics for variable selection criteria p-value r2 AIC / BIC lasso Giving regression a budget to use on coefficients which it uses on most important coefficients Have to scale first elastic net constrain combi...

ISYE 6501 FINAL EXAM WITH COMPLETE SOLUTION 2022/2023 1. Factor Based Models: classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model 2. Why limit number of factors in a model? 2 reasons: 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 3. Classical variable selection approaches: 1. Forward selection 2. Backwards eli...

Factor Based Models 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 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 1. Forward selection 2. Backwards elimination 3. Stepwise regression greedy algorithms Backward elimination...

Factor Based Models 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 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 Brainpower Read More Previous Play Next Rewind 10 seconds Move forward 10 seconds Unmute 0:01 / 0:15 Full screen Classical var...

OMSA Midterm Exam Questions With Complete Solutions Latest Updated 2023/2024. DOE - Answer- systematic method to determine the relationship between factors affecting a process and the output of that process. must make sure either: 1) 2 data sets have same mix 2) break down data into smaller tests that test all factors, not just one. forward selection - Answer- go step by step either narrowing or building a model -- begin with no factors. only allow new factors with p-value 0.1 or lower an...

ISYE 6501 REAL EXAM BRAND NEW!! 2023-2024 (200+ QUESTIONS AND CORRECT ANSWERS) VERIFIED ANSWERS when might overfitting occur - ANSWER- when the # of factors is close to or larger than the # of data points causing the model to potentially fit too closely to random effects Why are simple models better than complex ones - ANSWER- less data is required; less chance of insignificant factors and easier to interpret what is forward selection - ANSWER- we select the best new factor and see if i...

greedy algorithm - correct answer at each step, the algorithm does the thing that looks best without taking future options into consideration; more classical variable selection methods - correct answer stepwise - (forward, backward, combination) lasso elastic net available metrics for variable selection criteria - correct answer p-value r2 AIC / BIC lasso - correct answer Giving regression a budget to use on coefficients which it uses on most important coefficien...

ISYE 6501 FINAL EXAM WITH COMPLETE SOLUTION 2022/2023 1. Factor Based Models: classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model 2. Why limit number of factors in a model? 2 reasons: 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 3. Classical variable selection approaches: 1. Forward selection 2. Backwards eli...

ISYE 6501 FINAL EXAM WITH COMPLETE SOLUTION 2022/2023 1. Factor Based Models: classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model 2. Why limit number of factors in a model? 2 reasons: 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 3. Classical variable selection approaches: 1. Forward selection 2. Backwards eli...