CMAR » Historique » Révision 8
Révision 7 (François Rioult, 19/09/2012 18:58) → Révision 8/9 (François Rioult, 19/09/2012 19:10)
h1. CMAR - Classification with multiple association rules This Ariane graph implements CMAR, a well known supervised classification method with association rules. !https://forge.greyc.fr/attachments/195/cmar1.png! The parameters are the following: 1. the number of validations 2. the absolute minsup threshold 3. the number of accepted exceptions The input is the well know _iris_ database, which has 3 classes (on the first column). The cross-validation is handled by the _for_ loop, which will accumulate the result of the process. That is why there is a _touch_ input, which creates an empty file with the _echo -n_ command. * the XML may be viewed by a browser !https://forge.greyc.fr/attachments/196/cmar2.png! In the validation loop: * the database is first split in training and testing set with the _repartition_ operator * comments (lines starting with a sharp) are removed * the number of classes is computed with the purple macro, which cut the first columns, sorts it and counts * the classification decision is computed in the for loop on each class and is accumulated in the touched input * the classification result is a set of columns, one per class, containing the vote value for each instance. It is pasted to the train set. * a score operator computes various indicator in an XML file: recall, precision, score, confusion matrix, area under the ROC curve (ineffective when more than two classes) * the XML is accumulated !https://forge.greyc.fr/attachments/197/cmar3.png! The model is computed as follows: