profile shabazp/house price prediction

Updated Sun, August 20th - 12:10 AM GMT

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Install the Datmo CLI and clone this model.

$ datmo clone shabazp/house-price-prediction

House Prices Prediction

Datmo Model

Model to estimate housing prices

Kaggle House Prices: Advanced Regression Techniques

House Prices: Advanced Regression Techniques Competition on Kaggle

Shitao Wang submission version 1


This project requires Python 2.7 and the following Python libraries installed:

You will also need to have software installed to run and execute an iPython Notebook


All ipython notebook are used for data preprocessing, feature transforming and outlier detecting. All core scripts are in code folder, in which the ensemble learning script is in ensemble folder and base model script is in sing_model folder. All input data are in input folder and the detailed description of the data can be found in Kaggle.


For a single model run, navigate to the /code/single_model/ and run the following commands: python For a ensemble run, navigate to the /code/ensemble/ and run the following commands: python Make sure to change the data directory and the parameters accordingly before the model run.


Submission score on Kaggle leaderboard with different approaches.


Flow chart of the code.


4eyn7s3io65q second

Task: datmo task run "python"

Session: default

Code: asampat3090/datmo-house-prices-prediction#fdbbabe6

Environment: Dockerfile

Files: None

r8d0ks7im4dq exploratory

Task: datmo task run "jupyter notebook" --port 8888

Session: default

Code: asampat3090/datmo-house-prices-prediction#45a5025a

Environment: Dockerfile

Files: None



Snaphots: 2 8 months ago

Source Git Repository

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Updated: Invalid date GMT