Metadata-Version: 2.1
Name: housing_pred_mle
Version: 0.0.1
Summary: MLE Training Package
Home-page: https://github.com/abhirup77/mle-training
Author: Abhirup Sahoo
Author-email: abhirup.sahoo@tigeranalytics.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/abhirup77/mle-training/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data. 

## To set up the project

1. Clone the repository.


2. Create and activate virtual python development environment. On terminal, run


3. Install the package
    

4. Verify correct installation


5. Generate Sphinx Documentation



The following techniques have been used: 

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed
 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.


