Examples

Practical examples for using auto-sklearn.

Basic Examples

Examples for basic classification, regression, multi-output regression, and multi-label classification datasets.

Classification

Multi-output Regression

Regression

Multi-label Classification

Advanced Examples

Examples on customizing Auto-sklearn to ones use case by changing the metric to optimize, the train-validation split, giving feature types, using pandas dataframes as input and inspecting the results of the search procedure.

Interpretable models

Feature Types

Metrics

Model Explanation

Performance-over-time plot

Logging and debugging

Fit a single configuration

Resampling Strategies

Obtain run information

Metrics

Search Examples

Examples of changing the search procedure of Auto-sklearn.

Parallel Usage on a single machine

Sequential Usage

Parallel Usage: Spawning workers from the command line

Random Search

Successive Halving

Extension Examples

Examples of extending Auto-sklearn with custom components.

Extending Auto-Sklearn with Data Preprocessor Component

Extending Auto-Sklearn with Preprocessor Component

Restricting the number of hyperparameters for an existing component

Extending Auto-Sklearn with Regression Component

Extending Auto-Sklearn with Classification Component