Real Time Prediction of Cab Fare Using Machine Learning

For predicting the longer-term events predictive analysis use data which is an archive. For capturing the trends which are important mathematical model is used from past data. The model then uses present data to predict the longer-term or to derive actions to require optical outcomes tones of appreciation in recent time for predictive analytics thanks to development in support technology within areas of massive data in machine learning. Many industries use predictive analytics for making an accurate forecast like giving the amount of fare for the ride within the city. These resource planning are enabled by the forecast as an example, cab fare can be predicted more accurately. A lot of factors are taken into consideration for a taxi start-up company. This research work tries to know the patterns and use different methods for fare prediction. This research work is developed for predicting the cab fare amount within a certain city. The research work involves different steps like training, testing by using different variables like pickup, drop-off location for predicting cab fare.