Loocv Samenvattingen, Aantekeningen en Examens

THIS IS A COMPLETE NOTE FROM ALL BOOKS + LECTURE! Save your time for internships, other courses by studying over this note! Are you a 1st/2nd year of Business Analytics Management student at RSM, who want to survive the block 2 Machine Learning module? Are you overwhelmed with 30 pages of reading every week with brand-new terms and formulas? If you are lost in where to start or if you are struggling to keep up due to the other courses, or if you are just willing to learn about Machine Lea...

What are three problems that variable selection tries to minimize? - ANSWER-high dimensionality, multicollinearity, prediction vs explanatory high dimensionality - ANSWER-In linear regression, when the number of predicting variables P is large, we might get better predictions by omitting some of the predicting variables. Models with many predictors have... - ANSWER-low bias, high variance Models with few predictors have... - ANSWER-high bias but low variance prediction risk - ANSWER-...

Logistic Regression - ANSWER-Commonly used for modeling binary response data. The response variable is a binary variable, and thus, not normally distributed. In logistic regression, we model the probability of a success, not the response variable. In this model, we do not have an error term g-function - ANSWER-We link the probability of success to the predicting variables using the g link function. The g function is the s-shape function that models the probability of success with respect ...

ISYE 6501 9/5/2019 Homework 2, Georgia Tech, Graded A+ Document Content and Description Below ISYE 6501 9/5/2019 Homework 2 Question 3.1: Using the same data set (credit_card_ or credit_card_) as in Question 2.2, use the ksvm or kknn function to find a good classifi er: (a) using cross-validation (do this for the k-nearest-neighbors model; SVM is optional); Answer: To approach cross-validation for the KNN model, I attempted to leverage the kknn’s built-in cross-validation function: . This fu...