Report
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
| العنوان: | AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles |
|---|---|
| المؤلفون: | Weill, Charles, Gonzalvo, Javier, Kuznetsov, Vitaly, Yang, Scott, Yak, Scott, Mazzawi, Hanna, Hotaj, Eugen, Jerfel, Ghassen, Macko, Vladimir, Adlam, Ben, Mohri, Mehryar, Cortes, Corinna |
| سنة النشر: | 2019 |
| المجموعة: | Computer Science Statistics |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Statistics - Machine Learning |
| الوصف: | AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspired by the AdaNet algorithm (Cortes et al., 2017) which learns the structure of a neural network as an ensemble of subnetworks. We designed it to: (1) integrate with the existing TensorFlow ecosystem, (2) offer sensible default search spaces to perform well on novel datasets, (3) present a flexible API to utilize expert information when available, and (4) efficiently accelerate training with distributed CPU, GPU, and TPU hardware. The code is open-source and available at: https://github.com/tensorflow/adanet. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1905.00080 |
| رقم الانضمام: | edsarx.1905.00080 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |