Match each the following example datasets (X,y) on the left to the most logical type of supervised learning model to use on that dataset. Here, X is the input/predictors/features of the data while y is the output/target: multivariate linear regressior v X = (moms height in centimeters, dad's height in centimeters): y = (child's height in centimeters) X = (age in years, income in USD, years multiclass logistic regression of experience): y = (hired? true/false) X = (number of years experience binary logistic regression driving); y = (number of car accidents involved in -- Hint: this can be [ Choose assumed as continuous in this problem due to large amount) multivariate linear regression multiclass logistic regression X = (age, income, level of agreement with various political positions): y = binary logistic regression (Which of 4 candidates for whom they linear classification plan to vote) logistic polynomial regression univariate linear regression Previous multiclass polynomial regression Next