University Ranking Prediction System Using Machine Learning

In this research paper, we are representing a system of developing university ranking prediction system by analysing global university performance indicators. Here, we've used a uniform dataset of Times education world university rankings. Firstly, we perform pre-processing on the info to see whether the info is suitable to use or not and if not then we continue on further process to correct the dataset. to create the accurate and efficient prediction model, we split the ranking dataset into training and test data. Then, supported score or results of previous years we generate predicted score for every influential feature using our proposed outlier detection and rectilinear regression Algorithm. After it, all the schools are ranked globally supported the anticipated total score predicted by the model. Then, we evaluate the prediction system accuracy based the difference between the anticipated output vs actual output. eventually they are often stratified or guaranteed that our proposed university ranking prediction system is compatible to assess the upcoming global university ranking.