House Price Regression with R by Anastasiya KotelnikovaHouse Price Regression with R by Anastasiya Kotelnikova

House Price Regression with R

Anastasiya Kotelnikova

Data Analyst

Education

House Price Regression (R)

This project applies advanced regression techniques in R to predict house prices using a range of features. It was completed as part of the Data Analytics with R course at NJIT.

Dataset

Source: Kaggle House Prices: Advanced Regression Techniques

Format: CSV, ~1.5MB

Fields: 80+ features including square footage, neighborhood, year built, and materials

Techniques Used

Data cleaning and imputation

Handling skewness with log transformations

Feature engineering and selection

Ridge and Lasso regularization

Cross-validation and RMSE optimization

Model Performance

RMSE (Validation): 0.13

R² (Validation): 0.838

Project Structure

house-price-regression-r/
├── house_price_regression.R     # Main R script
├── data/                        # Raw dataset (optional)
├── outputs/                     # Model outputs and summaries
├── screenshots/                 # Visuals and plots
└── README.md                    # Project overview