Mr. Sumit Nigam

The capacity to screen the advancement for students' academic execution is a basic issue of the academic Group from claiming higher Taking in. An arrangement to dissecting students' comes about dependent upon group dissection and utilization standard measurable calculations with organize their scores information as stated by the level about their execution may be portrayed. In this paper, we also actualized k-mean and K-Medoids grouping algorithm for examining students' consequence information. Those model might have been consolidated for those deterministic model should dissect those students' effects of a private foundation clinched alongside % Iberia which is a great standard with screen the progression of academic execution about people for higher institutional to the reason for making an successful choice by those academic organizers.

This paper provides different kinds of techniques for lossless data compression and comparison between them. By eliminating redundant bits, data compression decreases the file size. In order to reduce the capacity needed for that data, it decreases the redundant bits in data representation and thus uses the bandwidth effectively to reduce the communication cost. Compression of data saves file volume, network bandwidth and speeds up the transfer speed as well. Lossless and Lossy are the two techniques for data compression. Lossless compression maintains the data properly.

Data mining is very emerging technology that is used in each and every system. Education data mining is very usefuldisciplines ,because the amount of data in education system is increasing day by day .in higher education is relatively new but its importance increases because of increasing database There are many approach for measuring students’ performance .data mining is one of them .with the help of data mining the hidden information in the database is get out which help for improvement of students performance education data mining is used to study the data available in education field to bring the hidden data i.e. important and useful information from it . There are many methods of data mining is used to analysis of students performance classification method like decision tree is most used to measure the students’performance. With the help of these it is easy to improve the result and future of students. More methods like clustering, regression, timeseries, and neural network can...

The capacity to screen the advancement for students' academic execution is a basic issue of the academic Group from claiming higher Taking in. An arrangement to dissecting students' comes about dependent upon group dissection and utilization standard measurable calculations with organize their scores information as stated by the level about their execution may be portrayed. In this paper, we also actualized k-mean and K-Medoids grouping algorithm for examining students' consequence information. Those model might have been consolidated for those deterministic model should dissect those students' effects of a private foundation clinched alongside % Iberia which is a great standard with screen the progression of academic execution about people for higher institutional to the reason for making an successful choice by those academic organizers.