numerox 0.0.9

Numerox is a Numerai tournament toolbox written in Python

Numerox is a Numerai tournament toolbox written in Python.

All you have to do is create a model. Take a look at model.py for examples.

Once you have a model numerox will do the rest. First download the Numerai dataset and then load it:

>>> import numerox as nx
>>> nx.download_dataset('numerai_dataset.zip')
>>> data = nx.load_zip('numerai_dataset.zip')
>>> data
region    train, validation, test, live
rows      637205
era       133, [era1, eraX]
x         50, min 0.0000, mean 0.5025, max 1.0000
y         mean 0.499924, fraction missing 0.3095

Let’s use the logistic regression model in numerox to run 5-fold cross validation on the training data:

>>> model = nx.model.logistic()
>>> prediction = nx.backtest(model, data, verbosity=1)
logistic(inverse_l2=1e-05)
      logloss   auc     acc     ystd
mean  0.693103  0.5159  0.5114  0.0008  |  region   train
std   0.000080  0.0289  0.0219  0.0000  |  eras     120
min   0.692874  0.4384  0.4446  0.0007  |  consis   0.7000
max   0.693323  0.5962  0.5626  0.0009  |  75th     0.6932

OK, results are good enough for a demo so let’s make a submission file for the tournament. We will fit the model on the train data and make our predictions for the tournament data:

>>> prediction = nx.production(model, data)
logistic(inverse_l2=1e-05)
      logloss   auc     acc     ystd
logistic(inverse_l2=1e-05)
      logloss   auc     acc     ystd
mean  0.693090  0.5178  0.5137  0.0010  |  region   validation
std   0.000060  0.0171  0.0140  0.0000  |  eras     12
min   0.692950  0.4891  0.4927  0.0010  |  consis   0.9167
max   0.693192  0.5556  0.5350  0.0010  |  75th     0.6931
>>> prediction.to_csv('logistic.csv')  # 6 decimal places by default

Examples

Have a look at the examples.

Install

Install with pip:

$ pip install numerox

After you have installed numerox, run the unit tests (please report any failures):

>>> import numerox as nx
>>> nx.test()

Requirements: python, setuptools, numpy, pandas, pytables, sklearn, requests, nose.

Resources

• Let’s chat

• See examples

• Check what’s new

• Report bugs

Sponsor

Thank you Numerai for funding the development of Numerox.

License

Numerox is distributed under the the GPL v3+. See LICENSE file for details. Where indicated by code comments parts of NumPy and SciPy are included in numerox. Their licenses appear in the licenses directory.