One Class Classifier for detecting positive cases while just trained on negative cases.
The Yeast dataset is obtained from KEEL data repository. his dataset contains 1004 number of instances and 8 numeric attributes. The last attribute is the class variable with two values positive and negative.
Building classifier(s) on the Yeast dataset that can identify the classes positive and negative with high performance. The training data has only “negative class”, while testing data has both the classes; negative and positive.
Three different methods have been applied on the data One Class SVM, Isolation Forest, and Elliptic Envelope.
