Skip to content

Latest commit

 

History

History
18 lines (8 loc) · 779 Bytes

File metadata and controls

18 lines (8 loc) · 779 Bytes

House Prices - Advanced Regression Techniques

Overview

This repo contains code for predicting house prices using advanced regression techniques. The model is implemented using XGBoost which is a popular gradient boosting algorithm.

Dataset

The dataset used in this project is sourced from the Kaggle competition House Prices - Advanced Regression Techniques. It consists of various features related to residential homes and their corresponding sale prices. The dataset is split into training and testing sets for model training and evaluation.

Data Description

  • train.csv: Training dataset containing features and sale prices.
  • test.csv: Testing dataset for making predictions.