Comparison of Undergraduate Students Performance Admitted Through Two Different Admission Criterion

Data mining is the most common way of utilizing factual strategies to uncover examples and bits of knowledge inside huge datasets. Commonly, the datasets utilized for information mining are huge to the point that would require days, weeks, or months for people to peruse or dissect. Subsequently, information mining frequently includes utilizing programs, Artificial Intelligence (AI), or man-made brainpower to accomplish the work. In any case, human examiners or data set directors frequently be involved to clean and process the information, so that datasets are ready for transformation and examination. With represented information, your information stewards should be proficient in these techniques to prepare machines to uncover these experiences and supervise their outcomes to confirm they are right. This article is a fast aide and introduction to data mining. In this paper, a brief comparison of the performance of undergraduate students has been analyzed, who got admission through two different admission criterions in a public sector engineering university. This research paper aims to identify the consequence of different admission policies on the future performance of engineering students.