An Open Source AutoML Benchmark

07/01/2019
by   Pieter Gijsbers, et al.
0

In recent years, an active field of research has developed around automated machine learning (AutoML). Unfortunately, comparing different AutoML systems is hard and often done incorrectly. We introduce an open, ongoing, and extensible benchmark framework which follows best practices and avoids common mistakes. The framework is open-source, uses public datasets and has a website with up-to-date results. We use the framework to conduct a thorough comparison of 4 AutoML systems across 39 datasets and analyze the results.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/25/2022

AMLB: an AutoML Benchmark

Comparing different AutoML frameworks is notoriously challenging and oft...
research
09/01/2017

Kafka versus RabbitMQ

Publish/subscribe is a distributed interaction paradigm well adapted to ...
research
08/17/2018

Benchmarking Automatic Machine Learning Frameworks

AutoML serves as the bridge between varying levels of expertise when des...
research
03/02/2017

MoleculeNet: A Benchmark for Molecular Machine Learning

Molecular machine learning has been maturing rapidly over the last few y...
research
09/12/2020

FuxiCTR: An Open Benchmark for Click-Through Rate Prediction

In many applications, such as recommender systems, online advertising, a...
research
03/23/2022

Towards Reproducible Network Traffic Analysis

Analysis techniques are critical for gaining insight into network traffi...
research
03/17/2022

A Framework and Benchmark for Deep Batch Active Learning for Regression

We study the performance of different pool-based Batch Mode Deep Active ...

Please sign up or login with your details

Forgot password? Click here to reset