- Hands-On Machine Learning with ML.NET
- Jarred Capellman
- 148字
- 2021-06-24 16:43:31
Choosing a linear regression trainer
When looking at the list of nine linear regression trainers ML.NET, it can be a bit daunting to ask which is the best.
For ML.NET linear regression trainers, by and large, the most popular are FastTree and LightGBM. The three FastTree algorithms utilize neighbor-joining and use heuristics to quickly identify candidate joins to build out a decision tree. LightGBM is a very popular linear regression algorithm that utilizes a Gradient-based One Side Sampling (GOSS) to filter out the data instances for finding a split value. Both trainers provide both quick training and predict times while also providing very accurate model performance. Also, more documentation, papers, and research are available with both of these algorithms.
The remaining five trainers are useful and worth a deep dive for experimentation, but overall you will likely find equal or greater success with LightGBM and FastTree.
推薦閱讀
- Oracle從入門到精通(第3版)
- DevOps:軟件架構師行動指南
- Oracle 11g從入門到精通(第2版) (軟件開發(fā)視頻大講堂)
- JMeter 性能測試實戰(zhàn)(第2版)
- Mastering Spring MVC 4
- C# 從入門到項目實踐(超值版)
- 跟老齊學Python:輕松入門
- Spring技術內(nèi)幕:深入解析Spring架構與設計原理(第2版)
- 實戰(zhàn)Java高并發(fā)程序設計(第2版)
- Mastering Adobe Captivate 7
- Vue.js光速入門及企業(yè)項目開發(fā)實戰(zhàn)
- 現(xiàn)代CPU性能分析與優(yōu)化
- Robot Framework Test Automation
- Developing Java Applications with Spring and Spring Boot
- 企業(yè)級Java現(xiàn)代化:寫給開發(fā)者的云原生簡明指南