Data Analysis is the main important subject in recent times as the ongoing demand for it is growing accordingly with the huge amounts of data we get from many sources, All the huge data we get should be properly analysed so that the information will be used accordingly to its needs. In this paper, the main objective is to analyse the data that is taken from uber related data from a csv file which is already available in the outside world. In addition to the analysing of data we are also including two features to our project, from which the first one is fare price detection and the second one goes with optimal allotment of a cab using appropriate machine learning algorithms. we used k- means clustering, Db Scan for optimal allotment of a cab. We used Linear regression, Logistic Regression ,Random Forest algorithms, Decision Tree Algorithm for fair price detection. We are also finding the best algorithm for increasing the accuracy of selection using unsupervised algorithms which is the best moto of our project. The additional feature we are wanting to add in to this mechanism of analysing the data is to use an android app developed by us in order to receive the required data from the users and perform various actions on it to obtain a best result for segmented two operations.
Keywords:Data analysis; uber data; fare price detection; machine learning algorithms; accuracy; unsupervised; android app
Citation : K.VinayKumar ,Santosh.N.C and Narasimha reddy soor “Data Analysis and Fair Price Prediction Using Machine Learning Algorithms ”, Journal of Computer Allied Intelligence (JCAI), vol.02, no.01, pp.26-45,2024.