Skip to main content

A package with helper scripts for complex DataRobot AutoTS use cases

Project description

datarobot_ts_helpers package

A library of helper scripts to support complex time-series modeling using DataRobot AutoTS software

Authors

Justin Swansburg, Jarred Bultema, Jess Lin

Description

The modeling of large scale time-series problems is possible directly within DataRobot software via the GUI or via R or Python modeling APIs. While the software is capable of modeling up to 1 million series per project and applying state of the art modeling techniques, often there is motivation to model aspects of a data science problem across multiple DataRobot projects. Motivation for this may include a desire to externally cluster similar series, apply different data manipulations or corrections, utilize different data sources, apply different differencing strategies, utilize different Feature Derivation Windows, or investigate different Forecast Distance ranges. Regardless of the reasons, internally we have found that performance can often be improved on large or complex time-series use cases by breaking a large, challenging problem into smaller pieces and modeling each of those pieces separately.

This is feasible directly using the R or Python modeling APIs, but the challenge quickly becomes one of software engineering and logistics to manage, compare, and store outputs of numerous projects that are part of a single use-case. The purpose of the ts_helpers package is to automate this logistical challenge and allow the DataRobot user to focus on applying different approaches to solve their use case, rather than focusing on the less interesting aspects of the problem.

Contents

This python package contains numerous functions to enable the user to easily scale from one to thousands of DataRobot projects starting with data preparation and continuing through modeling, model evaluation, iterative performance improvements, visualization of results, deployment of models, and serving ongoing predictions.

A detailed Table of Contents describes all functions present and the documentation string for each function. Detailed tutorials are also available to demonstrate the use of this ts_helpers package and all of the functions contained within.

Project details


Download files

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

Source Distribution

datarobot_ts_helpers-0.0.1.dev17.tar.gz (42.6 kB view details)

Uploaded Source

Built Distribution

datarobot_ts_helpers-0.0.1.dev17-py3-none-any.whl (48.5 kB view details)

Uploaded Python 3

File details

Details for the file datarobot_ts_helpers-0.0.1.dev17.tar.gz.

File metadata

  • Download URL: datarobot_ts_helpers-0.0.1.dev17.tar.gz
  • Upload date:
  • Size: 42.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.4

File hashes

Hashes for datarobot_ts_helpers-0.0.1.dev17.tar.gz
Algorithm Hash digest
SHA256 3e3ff6176609b4ac36e1fc87c45ab69943fc4fddd681c87879b7d8a3ae71a304
MD5 a8ae728b467a9af7ba4f0394e96876c8
BLAKE2b-256 5ef13c9190a9d9fc11c8a7bbd7ed5bdd4e6af84f0bb40935c56b5fd13a7f4224

See more details on using hashes here.

File details

Details for the file datarobot_ts_helpers-0.0.1.dev17-py3-none-any.whl.

File metadata

  • Download URL: datarobot_ts_helpers-0.0.1.dev17-py3-none-any.whl
  • Upload date:
  • Size: 48.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.4

File hashes

Hashes for datarobot_ts_helpers-0.0.1.dev17-py3-none-any.whl
Algorithm Hash digest
SHA256 37e42d05f355334593543745f59f18b9022462449a32d5fbff2c751d579029a7
MD5 7e2c3a9831308c2824704525a504b072
BLAKE2b-256 959d8569d7c0cd9930dfbb164a34b1e037af8c4c184a579cfdb5c29ae0490779

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page