This project requires Python 2.7 and the following Python libraries installed:
You will also need to have software installed to run and execute a Jupyter Notebook
The code is provided in the boston_housing.ipynb
notebook file. You will also need the included visuals.py
Python file and the housing.csv
dataset file to run the code.
The modified Boston housing dataset consists of 489 data points, with each datapoint having 3 features. This dataset is a modified version of the Boston Housing dataset found on the UCI Machine Learning Repository.
Features
RM
: average number of rooms per dwellingLSTAT
: percentage of population considered lower statusPTRATIO
: pupil-teacher ratio by town
Target Variable
4. MEDV
: median value of owner-occupied homes