贝叶斯网络库 [英] Library for Bayesian Networks
本文介绍了贝叶斯网络库的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
您好,数字打nch者
正如标题所暗示的,我正在寻找一个用于贝叶斯网络学习和推理的库.我已经找到了一些,但是我希望有个建议.
As the headline suggests, I am looking for a library for learning and inference of Bayesian Networks. I have already found some, but I am hoping for a recommendation.
快速概述中的要求:
- 最好用Java或Python编写
- (也是网络本身的)配置是a)可能的,并且b)通过代码(而不是仅通过GUI)的可能.
- 可用的源代码
- 项目仍在维护
- 功能越强大越好
您推荐哪个?
推荐答案
看看 Weka .它在我的脖子上很受欢迎……它是开源的并且用Java编写.
Have a look at Weka. It's kind of popular in my neck of the woods... It's open source and written in Java.
这将从摘要中向您介绍Weka中的贝叶斯网络:
This will tell you about bayesian networks in Weka, from the abstract:
- 贝叶斯结构学习 网络使用各种爬山 (K2,B等)和通用 (模拟退火,禁忌搜索) 算法.
- 本地分数指标 实施的;贝叶斯,BDe,MDL, 熵,AIC.
- 全球得分指标 实施的;遗漏简历,k折 简历和累积简历.
- 视情况而定 基于独立的因果恢复 可用的算法.
- 参数 使用直接估算进行估算,并 贝叶斯模型平均.
- GUI for 轻松检查贝叶斯网络.
- Structure learning of Bayesian networks using various hill climbing (K2, B, etc) and general purpose (simulated annealing, tabu search) algorithms.
- Local score metrics implemented; Bayes, BDe, MDL, entropy, AIC.
- Global score metrics implemented; leave one out cv, k-fold cv and cumulative cv.
- Conditional independence based causal recovery algorithm available.
- Parameter estimation using direct estimates and Bayesian model averaging.
- GUI for easy inspection of Bayesian networks.
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