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dc.contributor.supervisor Osborn, Wendy
dc.contributor.supervisor Fiske, Jo-Anne
dc.contributor.author Sun, Hongliang
dc.contributor.author University of Lethbridge. Faculty of Arts and Science
dc.date.accessioned 2009-07-08T20:06:54Z
dc.date.available 2009-07-08T20:06:54Z
dc.date.issued 2008
dc.identifier.uri https://hdl.handle.net/10133/738
dc.description viii, 38 leaves ; 29 cm. -- en
dc.description.abstract The report presents an implemention of a classification algorithm for the Institutional Analysis Project. The algorithm used in this project is the decision tree classification algorithm which uses a gain ratio attribute selectionmethod. The algorithm discovers the hidden rules from the student records, which are used to predict whether or not other students are at risk of dropping out. It is shown that special rules exist in different data sets, each with their natural hidden knowledge. In other words, the rules that are obtained depend on the data that is used for classification. In our preliminary experiments, we show that between 55-78 percent of data with unknown class lables can be correctly classified, using the rules obtained from data whose class labels are known. We feel this is acceptable, given the large number of records, attributes, and attribute values that are used in the experiments. The project results are useful for large data set analysis. en
dc.language.iso en_US en
dc.publisher Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2008 en
dc.relation.ispartofseries Project (University of Lethbridge. Faculty of Arts and Science) en
dc.subject Classification rule mining -- Alberta -- Lethbridge en
dc.subject Dropout behavior, Prediction of -- Analysis en
dc.subject Dropout behavior, Prediction of -- Computer programs en
dc.subject Pattern recognition systems en
dc.subject Data mining -- Alberta -- Lethbridge en
dc.subject Computer algorithms en
dc.subject College students -- Alberta -- Lethbridge en
dc.title Implementation of a classification algorithm for institutional analysis en
dc.type Thesis en
dc.publisher.faculty Arts and Science en
dc.publisher.department Mathematics and Computer Science en
dc.degree.level Masters


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