Naive Bayes classifier and Bayesian network classifier C++ implementation
Reference :
Usage:
./bayesian [training data file] [test data file] [configuration file] [method]
method :
0 : naive bayesian
1 : bayesian network
Example:
./bayesian breast_cancer_data/breast-cancer-wisconsin-400-records-train breast_cancer_data/breast-cancer-wisconsin-299-records-test breast_cancer_data/breast-cancer-wisconsin.cfg 0
Training & Test data are in CSV format:
[ attribute 1 of data 1 ],[ attribute 2 of data 1 ], ........ ,[ true result of data 1 ]
[ attribute 1 of data 2 ],[ attribute 2 of data 2 ], ........ ,[ true result of data 2 ]
[ attribute 1 of data 3 ],[ attribute 2 of data 3 ], ........ ,[ true result of data 3 ]
- For real prediction, don't need to provide true result. Need to pass second argument "0" for the "Predict" API.
Configuration file format:
[ number of training instance ] [ number of test instance ] [ number of attributes ]
[ attribute 1 is discrete(0) or continunous(1) ] [ attribute 2 is discrete(0) or continunous(1) ] ......
[ number of types for attributes 1 ] [ number of types for attributes 2 ] .......[ number of classes for prediction result ]
* For continuous data, the "number of types for attributes" won't matter.
* Bayesian Network DO NOT support continuous data for now.
Data set is acquired from UCI Machine Learning Repository
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