Objective: Analyze the provided dataset, applying appropriate data analysis techniques to achieve the specified task (e.g., Classification, Regression).
Requirements:
Task Execution:
Classification/Regression: Depending on the dataset chosen, perform classification or regression analysis. Be mindful of specific instructions associated with some datasets, such as file formats (.arff, .rar) or specific variables to be used or excluded.
Data Analysis: Conduct thorough data analysis which may include:
Data cleaning and preprocessing.
Exploratory data analysis to understand the variables.
Applying machine learning models to perform the task.
Evaluating model performance with appropriate metrics.
Documentation: Document your analysis process and results comprehensively. Your report should explain your choice of dataset, analysis steps, model selection, and insights from the data.
Submission: Complete your analysis and compile your findings into a detailed report (1500 words) and the R code. Ensure your submission is well-organized and clearly communicates your methods and results.