Cost Prediction for Online Home-Based Application Services by Using Linear Regression Techniques

Abstract

The number of services offered on-demand has grown significantly in past few years. On-demand home services aim to allow customers to avail a service immediately when in need anywhere and anytime. In the current scenario, people are buried up in a tough work culture, engaged with their busy schedules, and find no time to take care of the house or household activities. In such circumstances, to meet the expectations of a fantasized house without maintenance problems, they are in need of instant help. The developed portal is efficient in providing all the information of different business domains, with skilled employees. This portal is for users looking for online home services. The cost as per the latest market value can be predicted by machine learning model using linear regression algorithm. Various feature selector columns are used for different categories of target value. Any user can access this portal, as it is easy to operate. The data shown by the portal are up to date and updated real time. Service providers who are in the similar field will get benefited from it, as this Web site performs as an interface between users and service providers. The accomplishments of this work include, enhanced customer satisfaction, a unique customer experience, improved ratings and reviews, improvement in the existing services, and improved interaction between existing and potential customers. At last, the real-time feedback can be given by both the parties after user verification using token.