Learning Goal: I’m working on a data analytics question and need the explanation and answer to help me learn.
You are given a dataset named “Social_Network_Ads.csv” containing information about individuals’ ages, estimated salaries, and whether they made a purchase (0: No, 1: Yes). Your task is to perform a classification analysis using one of the following algorithms: K-Nearest Neighbors (KNN), Logistic Regression, or Support Vector Machine (SVM). Submit a report that includes the following information:
1. A brief description of the problem and the dataset.
2. Describe your selected classification method (KNN, Logistic Regression, or SVM) and its underlying concepts.
3. Data preparation steps.
4. Explain your training approach and parameter selections.
5. Present your model evaluation results using relevant metrics (e.g., accuracy, precision, recall, F1-score).
6. Discuss the findings of the study and any results regarding the model’s performance.
7. Create visualizations to illustrate your chosen algorithm’s performance.
8. Conclude by summarising your finding and the general lesson from the assignment.
Submission guidelines:
- The main submission document, containing your analysis, figures, interpretations, and conclusions, must be in Microsoft Word format( .docx).
- Please use a clear and concise naming convention for your files, including your name and the assignment number (e.g., “YourName_Assignment2.docx”).
- Ensure that key results are presented clearly in the Word document.
- If calculations were performed using Excel, Tableau, or Python, submit the respective files as supplementary materials alongside the Word document.
