The objective of this project is to analyze and classify the rainfall data provided by the Australian Government's Bureau of Meteorology using different classification algorithms. The dataset will be cleaned and preprocessed to remove any inconsistencies or missing values before being used to build the models.
The following classification algorithms will be used for this project:
- Linear Regression
- K-Nearest Neighbors (KNN)
- Decision Trees
- Logistic Regression
- Support Vector Machines (SVM)
The performance of each algorithm will be evaluated using appropriate metrics such as accuracy, precision, recall, and F1-score. The aim of this project is to compare the performance of these classification algorithms and determine the most suitable algorithm for the given dataset.
