Ensemble classifiers with a clustering and dynamic selection strategy and solve imbalance peoblem

LibD3C-1.1 is the upgrades for the software LibD3C.LibD3C is an ensemble classifiers with a clustering and dynamic selection strategy.For the LibD3C-1.1 ,it could solve imbalance data.

usage:

Usage is the same no mater windows or Linux

1.download the LibD3C_1.0.jar and classifier.xml(This file includes all base classifiers for LibD3C_1.0,you can even add other base classifier by yourself)

3.CrossValidation

2.1.balance data

 Java -jar LibD3C_1.0.jar -c fold-num trainFile

2.2.imbalance data

 Java -jar LibD3C_1.0.jar -m -c fold-num trainFile

fold-num is the crossValiditon folds. trainFile is the file path for the training data,softWare can only identify .arff file

3.prediction

(1)train model

Balance data

Java -jar LibD3C_1.1.jar -t trainFile

Imbalance data

Java -jar LibD3C_1.1.jar -m -t trainFile

-t means train model and the model would be saved in the same filePath(train.model) ,trainFile is the file path for the training data,resultFile is the file path save prediction result

(2)predict instance

Balance data

Java -jar LibD3C_1.1.jar -p train.model testFile resultFile

Imbalance data

Java -jar LibD3C_1.1.jar -m -p train.model testFile resultFile

-p means prediction and train.model is the filePath you trained before ,trainFile is the file path for the training data, resultFile is the file path save prediction result