Implementing machine learning in comparing the accuracy of classification algorithms in classifying levels of obesity
- Decision Tree
- Naive Bayes
- Amelia
- ggplot2
- GGally
- tidyverse
- knitr
- rpart
- rpart.plot
- party
- caret
Using the decision tree algorithm in classifying obesity data is better than using the Naive Bayes algorithm. By comparison accuracy:
- Decision Tree (party) : 91.96%
- Decision Tree (rpart) : 83.45%
- Naive Bayes : 70.69%