estimation-obesity-levels

Implementing machine learning in comparing the accuracy of classification algorithms in classifying levels of obesity

Datasets 💾

• https://archive.ics.uci.edu/ml/datasets/Estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition+

Algorithms 🤖

• Decision Tree
• Naive Bayes

Package 📦︎

• Amelia
• ggplot2
• GGally
• tidyverse
• knitr
• rpart
• rpart.plot
• party
• caret

Conclusion 💻︎

Using the decision tree algorithm in classifying obesity data is better than using the Naive Bayes algorithm. By comparison accuracy:

1. Decision Tree (party) : 91.96%
2. Decision Tree (rpart) : 83.45%
3. Naive Bayes : 70.69%