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README.md

PredictionIO Boston House Prices Template

Requirement

  • Spark 2.x

Getting Started

Create App on PIO

Create BHPApp application on PredictionIO:

pio app new --access-key BHP_TOKEN BHPApp

Import Data

Import data from boston_house_prices.csv.

python data/import_eventserver.py

Build Template

Build this template:

pio build

Run Jupyter

Launch Jupyter notebook and open eda.ipynb. (or you can create a new notebook to analyze data)

PYSPARK_PYTHON=$PYENV_ROOT/shims/python PYSPARK_DRIVER_PYTHON=$PYENV_ROOT/shims/jupyter PYSPARK_DRIVER_PYTHON_OPTS="notebook" pio-shell --with-pyspark

Run Train on Spark

Download Python code from eda.ipynb and put it to train.py. To execute it on Spark, run pio train with --main-py-file option.

pio train --main-py-file train.py

Deploy App

Run PredictionIO API server:

pio deploy

Predict

Check predictions from deployed model:

curl -s -H "Content-Type: application/json" -d '{"AGE":26.3, "B":390.49, "CHAS":0.0, "CRIM":0.08664, "DIS":6.4798, "INDUS":3.44, "LSTAT":2.87, "NOX":0.43700000000000006, "PTRATIO":15.2, "RAD":5.0, "RM":7.178, "TAX":398.0, "ZN":45.0}' http://localhost:8000/queries.json