Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training

Packet : 93317441naivebayes.rar filelist
朴素贝叶斯分类\朴素贝叶斯分类.doc
朴素贝叶斯分类\BaysClass\BaysClass.cpp
朴素贝叶斯分类\BaysClass\BaysClass.dsp
朴素贝叶斯分类\BaysClass\BaysClass.dsw
朴素贝叶斯分类\BaysClass\BaysClass.ncb
朴素贝叶斯分类\BaysClass\BaysClass.opt
朴素贝叶斯分类\BaysClass\BaysClass.plg
朴素贝叶斯分类\BaysClass\ReadMe.txt
朴素贝叶斯分类\BaysClass\StdAfx.cpp
朴素贝叶斯分类\BaysClass\StdAfx.h
朴素贝叶斯分类\BaysClass\Debug
朴素贝叶斯分类\BaysClass
朴素贝叶斯分类

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．