Apprentice-doa/House-Prices-Prediction-in-Nigeria-Model

# House-Prices-Prediction-in-Nigeria-Model ## Introduction Wazobia Real Estate Limited is a prominent real estate company operating in Nigeria. With a vast portfolio of properties, they strive to provide accurate and competitive pricing for houses. However, they have been facing challenges in accurately predicting the prices of houses in the current market. The objective of this project is to create a powerful and accurate predictive model that can estimate the prices of houses in Nigeria. By leveraging a comprehensive dataset, various factors that impact house prices, identify meaningful patterns are analyzed. he ultimate goal is to provide Wazobia Real Estate Limited with an effective tool to make informed pricing decisions and enhance their competitiveness in the market. ### N.B: This is a winning solution to the 2023 DSN & Microsoft Machine Learning hackathon. ## Problem Statement The project is aimed at using historical housing data in Nigeria to predict the price of houses in different states. It harnesses the combined the application of: + Features Engineering using Arithmetic operations, Geographical classification, Ranking + Features Encoding using Target encoding + Cross-validation. This project involved an in-depth understanding of the dataset provided which invloved the domain-level understanding of the features and their relationships. Data preprocessing began by filling in the missing values in the train dataset and applying features engineering to harness the relationship between the features. Other techniques like ranking, and geographical classification were employed to the features. ## Solution Overview ### Data preparation & preprocessing The dataset was taken through several techniques starting from the the filling of missing values with the median due to outliers in the dataset. Next, the missing values in the categorical features were dropped. ### Features Engineering data['room_conv'] = data['bedroom'] / data['bathroom'] data['size'] = d …