Modeling Madrid House Prices#
➡️ Modeling housing prices in Madrid
🔻 Objective:
🔸 Analyze how a series of variables influence the price of housing in Madrid, and select those that best predict it, using the linear regression model as a basis.
🔻 Developments:
️🔸 Data cleaning and preprocessing.
️🔸 Exploratory data analysis to preliminarily visualize relationships between the reassessment and the predictors.
️🔸 Presentation of the Linear Regression model.
️🔸 Adaptation of the implementation of the Linear Regression model of the Statsmodels framework to include interactions and dummy variables for categorical variables in an automated way
️🔸 Development of automated methods for the selection of predictors, based on significance test, likelihood ratio test, forward, backward and best subset selection algorithms.
️🔸 Selection of the best model using KFold Cross Validation.
️🔸 Estimation of future performance for the best model.
️🔸 Calculation of prediction intervals.
️🔸 Interpretation of the coefficients of the best model to analyze the relationship between the response and the predictors.