Data Mining Projects Repository

Overview

This repository serves as a collection of projects focused on data mining techniques, including data exploration, pattern recognition, and visualization. Each project applies different methodologies and tools to extract insights from various datasets. These projects are from assignments for the AD699 Data Mining course.

Projects

1. Vancouver City Service Requests Analysis

• Description: Analyzing service requests data from Vancouver to identify trends and patterns.
• Dataset Source: Vancouver’s Open Data Portal
• Technologies Used: R (tidyverse, dplyr, lubridate, ggplot2, ggthemes, leaflet), R Notebook
• Project Link: Vancouver City Requests Analysis

2. Forecasting the salaries of hockey players

• Description: Forecasting hockey player salaries by utilizing statistical analysis and machine learning methods.
• Technologies Used: R (tidyverse, dplyr, visualize, ggplot2, gplots, forecast), R Notebook
• Project Link: Hockey players salary prediction

3. K-Nearest Neighbors: You Like This Song...But Will George Like It?

• Description: Classification using k-NN algorithm
• Technologies Used: R (tidyverse, dplyr, caret, fnn, ggplot2), R Notebook
• Project Link: Spotify k-nn classifier

4. Naïve Bayes Classifier

• Description: Utilized the Naïve Bayes algorithm to classify and predict consumer disputes based on complaint data
• Technologies Used: R (tidyverse, dplyr, e1071, ggplot2), R Notebook
• Project Link: Consumer complaints analysis

Future Additions

More projects will be added over time, covering different aspects of data mining such as clustering, classification, and anomaly detection.