Chicago-Public-School-Students-Segmentation

Topic

This project aims to cluster students of a public school in Chicago. The data set available contains information about students contact, progress, family environment, soft skills scores... etc.

Objectives

• Treat the data set
• Understand the data and its imporant characteristics
• Cluster the students using different models

Model's used

• Kmeans
• DBSCAN
• Gaussian mixture
• Agglomerative hierarchical clustering

Evaluation matrices used

• Dendrogram
• Silhouette plot
• Elbow plot
• Silhouette score
• CH index
• DB index

Data source:

https://data.world/cityofchicago/chicago-public-schools-progress-report-cards-2011-2012/workspace/project-summary?agentid=cityofchicago&datasetid=chicago-public-schools-progress-report-cards-2011-2012