ADMISSION PREDICTION USING MULTIPLE LINEAR REGRESSION WITH PCA

ADMISSION PREDICTION USING MULTIPLE LINEAR REGRESSION WITH PCA

 G.VINESH*1, KAITEPALLI DHARANI *2, PEDDAPALLI NEESHMA*3,

SHRUTHI ANUGANTI*4, AND KAVELLI DHRUVANESHWAR *5

^*2*3*4*5 Authors, Department of Computer Science Engineering, CMR Technical Campus,

Kandlakoya(V ), Hyderabad, Telangana.

^*1Assistant Professor, Department of Computer Science Engineering, CMR Technical Campus,

Kandlakoya(V),Hyderabad,Telangana.

                                                                 ABSTRACT

This project is titled as “Admission Prediction using multiple linear regression with pca”. In today's education world there are many numbers of students who want to pursue higher education after engineering or any graduate degree course in abroad universities like USA, UK. Students who want to do master’s program in America have to write GRE and TOEFL. Once they have attended the exams which are one of the crucial factors they have to consider. So our goal is to develop a model using machine learning which will tell the students their chance of admission into a respective university. These models should consider all the crucial factors which plays a vital role in student admission process and should have high accuracy. The predicted output gives them a fair idea about their admission chances in a particular university.

   KEYWORDS:  Data preprocessing, Multiple linear regression, Principal components analysis, Admission    prediction, Machine learning.