House Price Prediction - R - Data Science

Description

  • Conducted data exploration to understand the dataset structure and key features influencing house prices.
  • Performed feature selection to identify the most impactful variables for the model.
  • Used a correlation matrix and scatterplot matrix to assess relationships between features.
  • Visualized data through boxplots to detect outliers and scatterplots to analyze trends.
  • Implemented univariate linear regression to predict house prices, focusing on sqft_living as a key predictor, alongside checking normality with density plots.
  • Converted the jupyter script file to HTML for prettier sharing

An error while displaying the image , check your browser settings

Model : XGBoost