This project aims to predict forest fires in the Algerian region by analyzing weather factors using various decision tree methods. Leveraging a dataset of forest fire observations from Bejaia and Sidi Bel-Abbes regions, I explore the predictive potential of weather characteristics on forest fires using algorithms such as rpart, party, C5.0, and caret in the R environment. Comparing these methods helps understand their respective strengths and weaknesses, aiding in selecting the most suitable model for the analysis goal. Evaluating model performance based on accuracy and interpretability provides valuable insights into predictive modeling of forest fires using decision trees.

This is a Dashboard for visualization of YouTube Video Trending in 2022 with Flexdashboard

Dashboard analysis about gap gender from job gender dataset