代写Acsc-Stat 300、代做R编程设计、代写R、代做data留学生-代写Algorithm 算法作业

Acsc-Stat 300

Lab 10 Assignment

The assignments must be in the correct format.

? All code you write in R must be compiled using R-Markdown with the output and answers

into MS-Word or PDF formats.

– The assignment must be done using R-Markdown. The output of this document will

include all the R code, R output and answers to the questions. Answers must be

written in full sentences.

Questions

Use the data file Lab10.RData for this assignment. Use the load() function to read the data.

1. This data has 200 observations. Before starting the variable y needs to be converted to

a factor. It is easiest to create a new data frame D1 containing the factor of y, and the

variables X1 and X2. Separate the data into a training set and a validation set each with

100 observations. Use a random number as the seed.

2. For the training data, plot X1 versus X2 denoting a different color for the values of Y. Does

the data appear to be separable? Please answer a little bit more than “Yes” or “No”.

3. Use the training data and cross validation to select the cost value Support Vector Classifi-

cation model.

(a) What is the best value for cost? How many support vector values are there? Plot the

best model on the training data.

(b) Plot the best model from 3a) on the validation points.

actual values for y (confusion table). What is the misclassification validation error?

4. Use the training data and cross validation to select the cost value and gamma for the

Support Vector Machine using a radial kernel.

(a) What are the recommended values for gamma and cost? Plot the best model on the

training data.

(b) Plot the best model from 4a) on the validation points.

actual values for y. What is the misclassification validation error?

5. Identify which of the two models you would use on this data and briefly state the reason

for your selection.