This project uses the Abalone dataset to build a regression tree model that predicts the age of abalones based on their physical measurements. The model was created using R and explores key steps like data cleaning, visualization, train/test splitting, tree building, pruning, and performance evaluation using RMSE. The goal was to understand how regression trees work in real-world scenarios and how feature importance impacts predictions.

Credit dataset

IRIS Dataset: Multi-class classification using KNN

Heart Failure dataset

Clustering

Matrix

Converting to meters

Using the Manhattan formula to create a data frame named Genes

The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and cut of each diamond.

Cars (plotting graphs)

Formulae for converting temperatures in Kelvin, Celsius or Fahrenheit.

Creating a toy dataset