Skip to main content
Join the official Python Developers Survey 2018 and win valuable prizes: Start the survey!

Scikit-learn style cross-validation classes for time series data

Project description

This package implements two cross-validation algorithms suitable to evaluate machine learning models based on time series datasets where each sample is tagged with a prediction time and an evaluation time.

Ressources

Installation

timeseriescv can be installed using pip:

>>> pip install timeseriescv

Content

For now the package contains two main classes handling cross-validation:

  • PurgedWalkForwardCV: Walk-forward cross-validation with purging.
  • CombPurgedKFoldCV: Combinatorial cross-validation with purging and embargoing.

Remarks concerning the API

The API is as similar to the scikit-learn API as possible. Like the scikit-learn cross-validation classes, the split method is a generator that yields a pair of numpy arrays containing the positional indices of the samples in the train and validation set, respectively. The main differences with the scikit-learn API are:

  • The split method takes as arguments not only the predictor values X, but also the prediction times pred_times and the evaluation times eval_times of each sample.
  • To stay as close to the scikit-learn API as possible, this data is passed as separate parameters. But in order to ensure that they are properly aligned, X, pred_times and eval_times are required to be pandas DataFrames/Series sharing the same index.

Check the docstrings of the cross-validation classes for more information.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
timeseriescv-0.2.tar.gz (6.7 kB) Copy SHA256 hash SHA256 Source None Sep 7, 2018

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page