Code for Quantitative Assessment of Factors Influencing Heat Vulnerability in Residential Areas using Machine Learning and UAV Data

Author: Ja Woon Gu Email: [e-mail] Date: 2024-07-22 Version: 1.0 Description: This script compares multiple regression models using GridSearchCV and RepeatedKFold cross-validation. The script identifies the best performing model based on the mean cross-validation score (neg_mean_squared_error). It performs residual analysis including normality, homoscedasticity, and autocorrelation checks. Models included: - DecisionTreeRegressor - ExtraTreesRegressor - AdaBoostRegressor - XGBRegressor - LGBMRegressor - CatBoostRegressor - RandomForestRegressor - GradientBoostingRegressor The best model's feature importances are calculated and plotted. Residuals are analyzed using Shapiro-Wilk, Levene's, and Durbin-Watson tests.