Student's performance in the context of data mining

Data Mining is an emerging field used in educational purposes to improve the perceptive and learning method of students. It focuses on recognizing, extracting and calculating data associated to the learning method and improving student's performance. Mining in a learning field is known as educational information mining which is fretful with exploring latest techniques to find out knowledge from educational fields. The purpose of our study is to evaluate the performance of students by taking different attributes like academic achievements (CGPA), gender, class test grade, environment of class, Fund/Scholarships/Private etc. In our research we will use classification and clustering techniques to analyze student performance. The techniques used in our work are decision tree, Bayesian classification-mean algorithms, neural networks, Naive's Bayes, Web based system and nearest neighbor methods.