- Machine Learning in Java
- AshishSingh Bhatia Bostjan Kaluza
- 86字
- 2021-06-10 19:29:59
Decision tree learning
Decision tree learning builds a classification tree, where each node corresponds to one of the attributes; edges correspond to a possible value (or intervals) of the attribute from which the node originates; and each leaf corresponds to a class label. A decision tree can be used to visually and explicitly represent the prediction model, which makes it a very transparent (white box) classifier. Notable algorithms are ID3 and C4.5, although many alternative implementations and improvements exist (for example, J48 in Weka).
推薦閱讀
- Splunk 7 Essentials(Third Edition)
- Dreamweaver CS3網(wǎng)頁制作融會(huì)貫通
- 城市道路交通主動(dòng)控制技術(shù)
- 現(xiàn)代機(jī)械運(yùn)動(dòng)控制技術(shù)
- Creo Parametric 1.0中文版從入門到精通
- 西門子S7-200 SMART PLC實(shí)例指導(dǎo)學(xué)與用
- 新手學(xué)電腦快速入門
- Statistics for Data Science
- 大數(shù)據(jù)技術(shù)基礎(chǔ):基于Hadoop與Spark
- JRuby語言實(shí)戰(zhàn)技術(shù)
- 深度學(xué)習(xí)原理與 TensorFlow實(shí)踐
- 算法設(shè)計(jì)與分析
- 中老年人學(xué)電腦與上網(wǎng)
- Web滲透技術(shù)及實(shí)戰(zhàn)案例解析
- Proteus從入門到精通100例