- 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
- 自動(dòng)控制工程設(shè)計(jì)入門(mén)
- 一本書(shū)玩轉(zhuǎn)數(shù)據(jù)分析(雙色圖解版)
- 精通Windows Vista必讀
- MicroPython Projects
- 21天學(xué)通C++
- AWS Administration Cookbook
- Deep Reinforcement Learning Hands-On
- Linux嵌入式系統(tǒng)開(kāi)發(fā)
- Working with Linux:Quick Hacks for the Command Line
- Silverlight 2完美征程
- 學(xué)練一本通:51單片機(jī)應(yīng)用技術(shù)
- 計(jì)算機(jī)組成與操作系統(tǒng)
- AMK伺服控制系統(tǒng)原理及應(yīng)用
- 新一代人工智能與語(yǔ)音識(shí)別
- 軟測(cè)之魂