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Adaboost extensions for cost-sentive classification
CSExtension 1
CSExtension 2
CSExtension 3
CSExtension 4
CSExtension 5
AdaCost
Boost
CostBoost
Uboost
CostUBoost
AdaBoostM1
Implementation of all the listed algorithms of the cluster "cost-sensitive classification".
They are the meta algorithms which requires base algorithms e.g. Decision Tree
Moreover,
Voting criteria is also required e.g. Minimum expected cost criteria
Input also requires to load an arff file and a cost matrix (sample arff and cost files are uploaded for users' reference)
This extension uses weka for classification and generates the classification model along with confusion matrix. For given dataset and cost matrix
Features
- cost sensitive data mining
- data mining
- adaboost
- cost sensitive adaboost
Project Samples
Categories
HMILicense
Creative Commons Attribution LicenseFollow Cost-sensitive Classifiers
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Link to the original research paper of this work is: http: //research.ijcaonline.org/volume44/number13/pxc3878677. pdf pls remove space before "//" and "pdf" in above url to make it work in your browser.