: This research-paper aims at comparing the accuracy of different classification algorithms used in supervised machine
learning. Classification Problem is about to find out in which class each example is related within a given dataset. It is used to
classify the data instances into different groups according to some characteristics. We used several famous supervised learning
algorithms - Logistic Regression, K-Nearest Neighbours (KNN), Decision Tree, Support Vector Machine (SVM), and Gradient
Boosting to classify the range of Mobile price. We have created multiple classifiers for Mobile Price classification and compared
their accuracy on the data taken from kaggle. Results are compared in terms of outcome accuracy score achieved from the
research experiment
