House Price Prediction Using XG-Boost Grid Search and Cross-Validation Methods
摘要
The primary factors influencing the variation in housing prices in different locations are the characteristics of the housing and the conditions of the area. This study will utilize the popular machine learning technique, XGBoost, along with grid-search and cross-validation techniques in deep learning. The chosen data set is appropriate as it provides adequate representation of both the range of house prices and the diversity.