• Madhura B Shetty
• L.Pratibha
• Lavanya.K
• Chaitra B S
• Sachin D N

The biggest defies that higher education institutions look currently is to increase students placement percentage. Educational institutes are in search of new technology that can increase the placement status of the institution. One efficient ways to improve the objective is to come up with the new acquaintance connected to the learning methods and objects. Using machine learning methods the information can be inferred after effective and chronological records which will be in the educational institute database. For the student implementation the data sets is of the information of the students from the past year. For rule identification the data is used for training model and for classification it is the testing model. This gives a reference system that foresees the students to get placed to any of these category i.e. Core Company, Dream Company, Mass Recruiters and Not Interested in Placements. This system supports the placement cell within an educational institute to categorize the potential of the students and consideration to increase students methodological and social skills. Further, the pre final and final years students of the B.E course can access this system to identify their position in placement individually. Through this they can come up with more hard work for getting placed in to the firms that belong to greater hierarchies.

Machine leaning, Naïve Bayes, Data Mining, Clustering, Placement.

"A Survey On Smart System For Student Placement Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.89-92, April-2019, Available :http://www.jetir.org/papers/JETIR1904I16.pdf

"A Survey On Smart System For Student Placement Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp89-92, April-2019, Available at : http://www.jetir.org/papers/JETIR1904I16.pdf