Predict Housing prices in boston with different Models. This repository is mainly for learning purpose and NOT for comercial-use.

Boston Housing Prediction is a python script that can predict the housing prices in boston with different models, the user can choose from.

You need to have python >= 3.5 installed.

To install the the script do(Press to view PYPI page):

$ pip install boston_housing_prediction

For older versions:
Alternatively download the latest release of boston-housing. Open the zip and in the code or boston_housing_prediction folder(folders have different names in different versions) you can see the script and its libaries.

You can run the programm with:

$ python -m boston_housing_prediction model_name

To see the help(for extra options) do:

$ python -m boston_housing_prediction -h

• 1.0.0

  • added Neural Network with pytorch

• 0.3.0

  • added normal_equation

• 0.2.3

  • choosing alpha is now possible
  • you can leave inputs empty and it will choose default values
  • bugfixes like #25 and more
  • uploaded pre-trained models that can be downloaded

• 0.2.2

  • fix negative input for training of model #24
  • fix negative output of predictions #24
  • optimized folder structure for PYPI #13
  • optimized some code.(comments, input)
  • documentation: changes in PYPI, coments in code

• 0.2.1

  • add normalization for data

• 0.2.0

  • release of polynomial_model

• 0.1.2

  • bugfixes #4, #5
  • serperated code in different files for more clarity. See code folder

• 0.1.1

  • added functionality to load models without training
  • plots are now outsourced and handled by a different kernel
  • dataset gets automatically downloaded when missing
  • v_data shows 4 different plots to describe the data(previously 2).

• 0.1.0

  • The first proper release
  • Realese of readme (Thanks @dbader)

• 0.0.1

  • Work in progress

• Add more models:

  • linear regression ✔️
  • polynomial_regression ✔️
  • normal equation ✔️
  • neural network ✔️

• Upload pre-trained models ✔️:

Distributed under the MIT license. See LICENSE for more information.

LICENSE Boston-housing

1. Fork it (https://github.com/LuposX/BostonHousingPrediction/fork)
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request