House-Price-Prediction

A linear regression model to predict house prices based on existing features.

Installation and Setup

git clone https://github.com/whoparthgarg/House-Price-Prediction

Data-set Examination

The data-set in CSV format is shown below:

• The training data-set has 3000 samples, 5 features and 1 target variable.
• The test data-set has 2000 samples and 5 features.
• The target variable is the price.

The data-set is available here: https://github.com/whoparthgarg/House-Price-Prediction/blob/main/USA_Housing.csv

Exploratory Data Analysis

Model Evaluation

Interpreting the coefficients:

• All features fixed, a 1 unit increase in Avg. Area Income is associated with an increase of $21.52 .
• All features fixed, a 1 unit increase in Avg. Area House Age is associated with an increase of $164883.28 .
• All features fixed, a 1 unit increase in Avg. Area Number of Rooms is associated with an increase of $122368.67 .
• All features fixed, a 1 unit increase in Avg. Area Number of Bedrooms is associated with an increase of $2233.80 .
• All features fixed, a 1 unit increase in Area Population is associated with an increase of $15.15 .

Predictions

Residual Histogram

Regression Evaluation Metrics