- Machine Learning in Java
- AshishSingh Bhatia Bostjan Kaluza
- 87字
- 2021-06-10 19:30:05
Cross-validation
Cross-validation splits the dataset into k sets of approximately the same size—for example, in the following diagram, into five sets. First, we use sets 2 to 5 for learning and set 1 for training. We then repeat the procedure five times, leaving out one set at a time for testing, and average the error over the five repetitions:
This way, we use all of the data for learning and testing as well, while avoiding using the same data to train and test a model.
推薦閱讀
- 基于C語言的程序設(shè)計(jì)
- Ansible Configuration Management
- 大數(shù)據(jù)管理系統(tǒng)
- Practical Ansible 2
- Seven NoSQL Databases in a Week
- 人工智能與人工生命
- 分?jǐn)?shù)階系統(tǒng)分析與控制研究
- Deep Reinforcement Learning Hands-On
- Windows Server 2008 R2活動(dòng)目錄內(nèi)幕
- Hands-On Data Warehousing with Azure Data Factory
- Linux Shell Scripting Cookbook(Third Edition)
- 渲染王3ds Max三維特效動(dòng)畫技術(shù)
- 軟件質(zhì)量管理實(shí)踐
- R Statistics Cookbook
- Microsoft 365 Mobility and Security:Exam Guide MS-101