Background: In most of the countries, students have to select a subject/stream in the secondary
education phase. Selection of subject/stream is crucial for students because further their career
proceeds according to their selection. Mostly subject/stream selection cannot be changed in the
further career. Inappropriate selection of subjects due to parental pressure, lack of information etc.
can lead to limited success in the selected stream. Guidance for subject/stream selection based on information
of successful scholars of their stream and information of students such as interest, family
background, previous education and other associated can enhance the success in career.
Methods: Data mining and machine learning based methods were developed on the above information.
Data from the different institutions and students of two different streams were used for training
and testing purposes. Different machine learning algorithms were used and methods with high
accuracy (86.72) were developed.
Result: Developed methods can be extended and used for different subject/stream selection.