Data Mining Techniques for School Failure and Dropout System

Provided by: International Journal of Ethics in Engineering & Management Education (IJEEE)
Topic: Big Data
Format: PDF
Data mining techniques are applied to predict college failure and bum of the student. This is method uses real data on middle-school students for prediction of failure and drop out. It implements white-box classification strategies, like induction rules and decision trees or call trees. Call tree could be a call support tool that uses tree-like graph or a model of call and their possible consequences. A call tree is a flowchart-like structure in which internal node represents a "Test" on an attribute. Attribute is the real information of students that is collected from college in middle or pedagogy, each branch represents the outcome of the test and each leaf node represents a class label.

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