This project clusters white wines based on their chemical properties to understand their relationship with quality ratings, using techniques like k-means and PCA.

Clustering tutorial in R for UConn's Social-Ecological-Environmental (SEE) Lab

This project carried out in R applies PCA for dimensionality reduction and K-Means for clustering on the IRIS dataset. It includes EDA, PCA variance analysis, and cluster evaluation using ggplot2 and factoextra. Additionally, it visualizes the impact of reducing dimensions on clustering.

Customer Segmentation using R

Segmentação de clientes com base em análise RFM

Project uses K-Means clustering to analyze mall customers based on spending behavior and annual income

Clustering to find customer segment of the Boston based ride sharing program Hubway

Análisis de pandemia utilizando base de datos .csv

Analyzing key air quality variables with R through visualizations and statistical methods.

Perform cluster analysis on household electricity consumption data using K-means clustering in R

Tutorial code for performing PCA (with mathematical explanation) on breast cancer features computed from digitized images of fine needle aspirate (FNA) of a breast mass. Center the data, calculate correlation matrix, compute principal components, visualize and interpret results.