> library(party) > myFormula <- Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width > iris_ctree <- ctree(myFormula, data=trainData) > table(predict(iris_ctree), trainData$Species) What is the process in the above code in R? options: Building a decision tree for the iris data with function ctree() in package party by using myFormula to put Species as the target variable and all other variables are independent variables, and then using predict() function to check the prediction. Building a linear regression model for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction. Building a random forest for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction. Building a non-linear regression for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 13CYU

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Question

> library(party)

> myFormula <- Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width

> iris_ctree <- ctree(myFormula, data=trainData)

> table(predict(iris_ctree), trainData$Species)

What is the process in the above code in R?

options:

	Building a decision tree for the iris data with function ctree() in package party by using myFormula to put Species as the target variable and all other variables are independent variables, and then using predict() function to check the prediction.
	Building a linear regression model for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction.
	Building a random forest for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction.
	Building a non-linear regression for the iris data with function ctree() in package party by using myFormula to put Species as dependent variable and all other variables are independent variables, and then using predict() function to check the prediction.

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