xgboost basic

An basic example to show using xgboost.

$ python -V
Python 3.6.0 :: Anaconda 4.3.1 (64-bit)

If xgboost is not installed, install it by running

$ pip install xgboost

$ python -V
Python 3.6.0 :: Anaconda 4.3.1 (64-bit)

>>> print(xgboost.__version__)
0.6

Pima Indians diabetes dataset

You can learn more about this dataset on the UCI Machine Learning Repository website

Basiclly, this dataset is comprised of 8 input variables that describe medical details of patients and one output variable to indicate whether the patient will have an onset of diabetes within 5 years.

Download dataset from here

$ wget https://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data

Steps

$ python split_datasets.py

Split the whole datasets into two sets train.csv and test.csv. train.csv is for training model and test.csv is for testing the trained model.

$ python create_model.py

Train model using xgboost and save it into pima_model.pkl

$ python predict.py

Accuracy: 81.17%

Based on the saved mode pima_model.pkl, make predictions on the test dataset test.csv and test the model.