RETAIL PRICE PREDICTION USING LINEAR REGRESSION

RETAIL PRICE PREDICTION USING LINEAR REGRESSION

MS. M BANUPRIYA 1 , CHETANAPPRIYA K.L 2 , MAHESWARAN M 3 , MAYURI K.B 4 , RAJARATNAM KAWSHIKA 5

1 Assistant Professor, Dept of Computer Science and Engineering, Saranathan College of Engineering, Tiruchirappalli, Tamil Nadu, India

2-5 Student, Dept of Computer Science and Engineering, Saranathan College of Engineering, Tiruchirappalli, Tamil Nadu, India

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Abstract — Machine Learning plays a vital role from past years in normal speech command, product recommendation as well as in the medical field. It also provides better customer services and a safer automobile system. This shows that ML is a trending technology in almost all the fields. People are looking forward to buy a new home and car with their budgets by analyzing the market. By using certain Machine learning algorithms, a price predicting model can be implemented. This model will help people to put resources into a bequest without moving towards a broker. This project demonstrates the usage of machine learning algorithm in the prediction of prices using dataset downloaded from Kaggle. This model provides a review of the usage of existing machine learning algorithms on a dataset and tries to implement this prediction engine for real-life usage by users. The findings are obtained using linear regression algorithm. Machine learning Algorithms are used because they provide us with continuous value as output and not a categorized value. Because of which it is possible to predict the actual price rather than the price range of a car or house.

Key Words: Machine learning, price prediction, linear regression, regression analysis, feature