Original paper
Scaling tree-based automated machine learning to biomedical big data with a feature set selector
Abstract
Motivation Automated machine learning (AutoML) systems are helpful data science assistants designed to scan data for novel features, select appropriate supervised learning models and optimize their parameters. For this purpose, Tree-based Pipeline Optimization Tool (TPOT) was developed using strongly typed genetic programing (GP) to recommend an optimized analysis pipeline for the data scientist’s prediction problem. However, like other AutoML...
Paper Details
Title
Scaling tree-based automated machine learning to biomedical big data with a feature set selector
Published Date
Jun 4, 2019
Journal
Volume
36
Issue
1
Pages
250 - 256
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History