Bella Capelli A Paul Mitchell R Studio Classification and Prediction Models Project Need attached RStudio assignment completed………………………..

Bella Capelli A Paul Mitchell R Studio Classification and Prediction Models Project Need attached RStudio assignment completed……………………………………………………………….data can be downloaded from herehttps://www.mediafire.com/file/hs6xedesw1wvfc5/Car… Notes:
• First, please re-save this document on your computer, RENAMING the file to contain your
last name.
LAST NAME =AMAECHI
• Point values of each part are shown below; 10 points will be allocated for the quality of
your business writing (organization, clarity, grammar, etc.).
• Type or paste your responses into the boxes below. The boxes will expand to fit your
answers.
Clasification and Prediction Models Model
•
Read the Cardiotocographic.csv data file into RStudio. Make sure to use NSP as a ‘factor’ or
‘categorical’ variable for this assignment. Run set.seed(XXX) by using last three digits of your student
ID in place of XXX followed by partitioning of the dataset into training (50%) and testing (50%).
Report on how many cases of N, S, and P exist in the training and testing data. In addition, provide the
code used. (10 pts). SET.SEED(426)
•
Develop a multinomial logistic regression model for predicting NSP based on the training dataset and
report the final model, related code, prediction equations, confusion matrix for training and test
datasets. What conclusions can you derive? (20 points):
•
Develop a decision tree for predicting NSP using training dataset and report the final tree, related
code, confusion matrix for both training and test datasets. What conclusions can you derive (20
points):
•
Develop a random forest model for predicting NSP using training dataset and provide related code,
confusion matrix for both training and test datasets. What conclusions can you derive (20 points):
•
Develop a support vector machine model for predicting NSP using training dataset and provide related
code, confusion matrix for both training and test datasets. What conclusions can you derive (20
points):
•
Which classification and prediction method do you find to be the best and why? (10 points):
PLEASE COMMENTS AND CONCLUSIONS ARE VERY IMPORTANT

Purchase answer to see full
attachment