Problem Statement

You are given a dataset from a university where applications are accepted for the admission of students based on their scores on the entrance test. You have to build a KNN Classifier to predict the selection of a student. Your task is to implement a KNN Classifier to find the selection of a candidate and print the accuracy score of the model (rounded off to 2 decimals). Notes & Constraints - You must set the Train Test Split Ratio = 0.33 and Random State = 42. - You must normalize the data using a standard scaler. - For KNN: n_neighbors = 7, metric = 'minkowski', algorithm = 'brute', and use Euclidean Distance (which corresponds to p = 2 in the Minkowski metric). - The input data is given as comma-separated values. Use pd.read_csv(sys.stdin) to read the dataset. Data Dictionary - Physics: Score obtained by the student in Physics, ranging from 75-100. - Chemistry: Score obtained by the student in Chemistry, ranging from 75-100. - Mathematics: Score obtained by the student in Mathematics