Sample code for coding practice
Project description
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.
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.
To excute the script
python < scriptname.py ># mle-training mle-training
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for housing_library_5492-0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | adb1f4f52e12ba71aee8fac31b9a452f530d4de26790a1086af0b46935d5650a |
|
MD5 | 0432a4d7f63870f7808d492757b4fb76 |
|
BLAKE2b-256 | eee709893a0f7c476faaa91c2143bf6fc676f8eec2b1736031a2d15085e1876e |